Introduction

For one of my machine learning classes we had a project that consumed financial data. I have extended that project to use machine learning to see if an indicator, or predictor, can be found that identifies market tops that occur prior to recessions. Then I use the model to build a trading strategy and backtest it to see how it performs.

Get Economic and Financial Data

Acquiring the data consists of two steps. First the code pulls the data into zoo objects which are then collapsed into a single data frame (df.data). Features are extracted from these series and added to the df.data data frame.

Sample call to pull economic data

Data is pulled from several sources include FRED, yahoo, and Google. The code below shows an example that pulls in the consumer price index (CPI) from the FRED. I pull data using quantmod, Quandl, and some manual extractions stored in spreadsheets.

# Consumer Price Index for All Urban Consumers: All Items
if (bRefresh == TRUE) {
  getSymbols("CPIAUCSL", src = "FRED", auto.assign = TRUE)
}
## [1] "CPIAUCSL"
## [1] "CPIAUCSL"
## [1] "USREC"
## [1] "UNRATE"
## [1] "PCEPI"
## [1] "CCSA"
## [1] "CCNSA"
## [1] "NPPTTL"
## [1] "U6RATE"
## [1] "PAYNSA"
## [1] "TABSHNO"
## [1] "HNONWPDPI"
## [1] "INDPRO"
## [1] "RRSFS"
## [1] "RSALES"
## [1] "W875RX1"
## [1] "RPI"
## [1] "PCOPPUSDM"
## [1] "NOBL"
## [1] "SCHD"
## [1] "PFF"
## [1] "HPI"
## [1] "GSFTX"
## [1] "LFMIX"
## [1] "LFMCX"
## [1] "LFMAX"
## [1] "LCSIX"
## [1] "BSV"
## [1] "VBIRX"
## [1] "BIV"
## [1] "VFSUX"
## [1] "LTUIX"
## [1] "PTTPX"
## [1] "NERYX"
## [1] "STIGX"
## [1] "HLGAX"
## [1] "FTRGX"
## [1] "THIIX"
## [1] "PTTRX"
## [1] "BFIGX"
## [1] "VTWO"
## [1] "EIFAX"
## [1] "ASDAX"
## Warning: ASDAX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## [1] "TRBUX"
## [1] "PRVIX"
## [1] "PRWCX"
## [1] "ADOZX"
## [1] "MERFX"
## [1] "CMNIX"
## [1] "CIHEX"
## [1] "IMPCH"
## [1] "EXPCH"
## [1] "IMPMX"
## [1] "EXPMX"
## [1] "HSN1FNSA"
## [1] "HNFSUSNSA"
## [1] "BUSLOANS"
## [1] "TOTCI"
## [1] "BUSLOANSNSA"
## [1] "REALLNNSA"
## [1] "REALLN"
## [1] "RELACBW027NBOG"
## [1] "RELACBW027SBOG"
## [1] "RREACBM027NBOG"
## [1] "RREACBM027SBOG"
## [1] "RREACBW027SBOG"
## [1] "RREACBW027NBOG"
## [1] "MORTGAGE30US"
## [1] "CONSUMERNSA"
## [1] "TOTLLNSA"
## [1] "DPSACBW027SBOG"
## [1] "DRCLACBS"
## [1] "TOTCINSA"
## [1] "SRPSABSNNCB"
## [1] "ASTLL"
## [1] "FBDILNECA"
## [1] "ASOLAL"
## [1] "ASTMA"
## [1] "ASHMA"
## [1] "ASMRMA"
## [1] "ASCMA"
## [1] "ASFMA"
## [1] "CCLBSHNO"
## [1] "FBDSILQ027S"
## [1] "FBLL"
## [1] "NCBDBIQ027S"
## [1] "DGS10"
## [1] "^TNX"
## Warning: ^TNX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## Warning: CL=F contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## [1] "DGS30"
## [1] "DGS1"
## [1] "DGS2"
## [1] "TB3MS"
## [1] "DTB3"
## [1] "^IRX"
## Warning: ^IRX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## [1] "DCOILWTICO"
## [1] "DCOILBRENTEU"
## [1] "NEWORDER"
## [1] "ALTSALES"
## [1] "ICSA"
## [1] "^GSPC"
## [1] "FXAIX"
## [1] "FTIHX"
## [1] "MDIZX"
## [1] "DODIX"
## [1] "^RLG"
## Warning: ^RLG contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## [1] "^DJI"
## [1] "^STOXX50E"
## Warning: ^STOXX50E contains missing values. Some functions will not work if
## objects contain missing values in the middle of the series. Consider using
## na.omit(), na.approx(), na.fill(), etc to remove or replace them.
## [1] "EFA"
## [1] "GDP"
## [1] "FNDEFX"
## [1] "FDEFX"
## [1] "GDPNOW"
## [1] "GDPC1"
## [1] "GDPDEF"
## [1] "VIG"
## [1] "WLRRAL"
## [1] "FEDFUNDS"
## [1] "GPDI"
## [1] "W790RC1Q027SBEA"
## [1] "MZMV"
## [1] "M1"
## [1] "M2"
## [1] "OPHNFB"
## [1] "IPMAN"
## [1] "IWD"
## [1] "GS5"
## [1] "PSAVERT"
## [1] "VIXCLS"
## [1] "VXX"
## [1] "HOUST1F"
## [1] "GFDEBTN"
## [1] "HOUST"
## [1] "HOUSTNSA"
## [1] "EXHOSLUSM495S"
## [1] "MSPUS"
## [1] "UMDMNO"
## [1] "DGORDER"
## [1] "CSUSHPINSA"
## [1] "GFDEGDQ188S"
## [1] "FYFSD"
## [1] "FYFSGDA188S"
## [1] "GDX"
## [1] "XLE"
## [1] "GSG"
## [1] "WALCL"
## [1] "OUTMS"
## [1] "MANEMP"
## [1] "PRS30006163"
## [1] "BAMLC0A3CA"
## [1] "AAA"
## [1] "SOFR"
## [1] "SOFRVOL"
## [1] "SOFR99"
## [1] "SOFR75"
## [1] "SOFR25"
## [1] "SOFR1"
## [1] "OBFR"
## [1] "OBFR99"
## [1] "OBFR75"
## [1] "OBFR25"
## [1] "OBFR1"
## [1] "RPONTSYD"
## [1] "IOER"
## [1] "WRESBAL"
## [1] "EXCSRESNW"
## [1] "ECBASSETS"
## [1] "EUNNGDP"
## [1] "CEU0600000007"
## [1] "CURRENCY"
## [1] "WCURRNS"
## [1] "BOGMBASE"
## [1] "PRS88003193"
## [1] "PPIACO"
## [1] "PCUOMFGOMFG"
## [1] "POPTHM"
## [1] "POPTHM"
## [1] "CLF16OV"
## [1] "LNU01000000"
## [1] "LNU03000000"
## [1] "UNEMPLOY"
## [1] "RSAFS"
## [1] "FRGSHPUSM649NCIS"
## [1] "BOPGTB"
## [1] "TERMCBPER24NS"
## [1] "A065RC1A027NBEA"
## [1] "PI"
## [1] "PCE"
## [1] "A053RC1Q027SBEA"
## [1] "CPROFIT"
## [1] "SPY"
## [1] "MDY"
## [1] "EES"
## [1] "IJR"
## [1] "VGSTX"
## [1] "VFINX"
## [1] "VOE"
## [1] "VOT"
## [1] "TMFGX"
## Warning: TMFGX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## [1] "IWM"
## [1] "ONEQ"
## [1] "FSMAX"
## [1] "FXNAX"
## [1] "HAINX"
## [1] "HNACX"
## [1] "VEU"
## [1] "VEIRX"
## [1] "BIL"
## [1] "IVOO"
## [1] "VO"
## [1] "CZA"
## [1] "VYM"
## [1] "ACWI"
## [1] "SLY"
## Warning: SLY contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## [1] "QQQ"
## [1] "HYMB"
## [1] "GOLD"
## [1] "BKR"
## [1] "SLB"
## [1] "HAL"
## [1] "IP"
## [1] "PKG"
## [1] "UPS"
## [1] "FDX"
## [1] "T"
## [1] "VZ"

Load up the EIA data

Load rig count data

The Baker Hughes rig count numbers

USDA data

Loading in farm data

## Warning in read_fun(path = enc2native(normalizePath(path)), sheet_i = sheet, :
## Expecting numeric in E3 / R3C5: got a date
## New names:
## * `` -> ...1
## * `` -> ...2
## * `` -> ...3
## * `` -> ...4
## * `` -> ...5
## * ...
## Warning: NAs introduced by coercion

Loading in Silverblatt’s S&P 500 spreadsheet starting with the quarterly data.

## New names:
## * `` -> ...2
## * `` -> ...3
## * `` -> ...5
## * `` -> ...6
## * `` -> ...7

Now load in the estimates

## New names:
## * `` -> ...2
## * `` -> ...3
## * `` -> ...4
## * `` -> ...5
## * `` -> ...6
## * ...

Covid 19 Data

Get the Covid-19 data from JHU

## Rows: 919308 Columns: 15
## -- Column specification ------------------------------------------------------------------------------------------------
## Delimiter: ","
## chr  (8): province, country, type, iso2, iso3, combined_key, continent_name,...
## dbl  (6): lat, long, cases, uid, code3, population
## date (1): date
## 
## i Use `spec()` to retrieve the full column specification for this data.
## i Specify the column types or set `show_col_types = FALSE` to quiet this message.
## Downloading GitHub repo RamiKrispin/coronavirus@master
##   
  
  
v  checking for file 'C:\Users\Rainy\AppData\Local\Temp\Rtmpg1ESs7\remotes607415d77954\RamiKrispin-coronavirus-b286a3c/DESCRIPTION'
## 
  
  
  
-  preparing 'coronavirus': (1.5s)
##    checking DESCRIPTION meta-information ...
  
   checking DESCRIPTION meta-information ... 
  
v  checking DESCRIPTION meta-information
## 
  
  
  
-  checking for LF line-endings in source and make files and shell scripts (344ms)
## 
  
-  checking for empty or unneeded directories
## 
  
  
  
-  building 'coronavirus_0.3.32.tar.gz'
## 
  
   
## 
## Caught an warning!
## <simpleWarning: package 'coronavirus' is in use and will not be installed>
## `summarise()` has grouped output by 'country'. You can override using the
## `.groups` argument.

## Warning: Removed 3 row(s) containing missing values (geom_path).

Feature Extraction

With the raw data downloaded, some of the interesting features can be extracted. The first step is reconcile the time intervals. Some of the data is released monthly and some daily. I chose to interpolate all data to a daily interval. The first section of code adds the daily rows to the dataframe.

The code performs interpolation for continuous data or carries it forward for binary data like the recession indicators.

source("calcInterpolate.r")
df.data <- calcInterpolate(df.symbols)
## Warning in merge.xts(xtsData, get(df.symbols$string.symbol[idx])): NAs
## introduced by coercion

## Warning in merge.xts(xtsData, get(df.symbols$string.symbol[idx])): NAs
## introduced by coercion

## Warning in merge.xts(xtsData, get(df.symbols$string.symbol[idx])): NAs
## introduced by coercion

Truncate data

Create aggregate series

Some analysis requires that two or more series be combined. For example, normallizing debt by GDP to get a sense of the proportion of debt to the total economy helps understand the debt cycle.

Year over year, smoothed derivative, and log trends tend to smooth out seasonal variation. It gets used so often that I do this for every series downloaded.

source("calcFeatures.r")
lst.df <- calcFeatures(df.data, df.symbols)
## [1] "USREC has zero or negative values. Log series will be zero."
## [1] "GSFTX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMIX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMCX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMAX.Volume has zero or negative values. Log series will be zero."
## [1] "LCSIX.Volume has zero or negative values. Log series will be zero."
## [1] "VBIRX.Volume has zero or negative values. Log series will be zero."
## [1] "VFSUX.Volume has zero or negative values. Log series will be zero."
## [1] "LTUIX.Volume has zero or negative values. Log series will be zero."
## [1] "PTTPX.Volume has zero or negative values. Log series will be zero."
## [1] "NERYX.Volume has zero or negative values. Log series will be zero."
## [1] "STIGX.Volume has zero or negative values. Log series will be zero."
## [1] "HLGAX.Volume has zero or negative values. Log series will be zero."
## [1] "FTRGX.Volume has zero or negative values. Log series will be zero."
## [1] "THIIX.Volume has zero or negative values. Log series will be zero."
## [1] "PTTRX.Volume has zero or negative values. Log series will be zero."
## [1] "BFIGX.Volume has zero or negative values. Log series will be zero."
## [1] "EIFAX.Volume has zero or negative values. Log series will be zero."
## [1] "ASDAX.Volume has zero or negative values. Log series will be zero."
## [1] "TRBUX.Volume has zero or negative values. Log series will be zero."
## [1] "PRVIX.Volume has zero or negative values. Log series will be zero."
## [1] "PRWCX.Volume has zero or negative values. Log series will be zero."
## [1] "ADOZX.Volume has zero or negative values. Log series will be zero."
## [1] "MERFX.Volume has zero or negative values. Log series will be zero."
## [1] "CMNIX.Volume has zero or negative values. Log series will be zero."
## [1] "CIHEX.Volume has zero or negative values. Log series will be zero."
## [1] "SRPSABSNNCB has zero or negative values. Log series will be zero."
## [1] "TNX.Volume has zero or negative values. Log series will be zero."
## [1] "CLF.Open has zero or negative values. Log series will be zero."
## [1] "CLF.Low has zero or negative values. Log series will be zero."
## [1] "CLF.Close has zero or negative values. Log series will be zero."
## [1] "CLF.Volume has zero or negative values. Log series will be zero."
## [1] "CLF.Adjusted has zero or negative values. Log series will be zero."
## [1] "DTB3 has zero or negative values. Log series will be zero."
## [1] "IRX.Open has zero or negative values. Log series will be zero."
## [1] "IRX.High has zero or negative values. Log series will be zero."
## [1] "IRX.Low has zero or negative values. Log series will be zero."
## [1] "IRX.Close has zero or negative values. Log series will be zero."
## [1] "IRX.Volume has zero or negative values. Log series will be zero."
## [1] "IRX.Adjusted has zero or negative values. Log series will be zero."
## [1] "DCOILWTICO has zero or negative values. Log series will be zero."
## [1] "FXAIX.Volume has zero or negative values. Log series will be zero."
## [1] "FTIHX.Volume has zero or negative values. Log series will be zero."
## [1] "MDIZX.Volume has zero or negative values. Log series will be zero."
## [1] "DODIX.Volume has zero or negative values. Log series will be zero."
## [1] "RLG.Volume has zero or negative values. Log series will be zero."
## [1] "STOXX50E.Volume has zero or negative values. Log series will be zero."
## [1] "GDPNOW has zero or negative values. Log series will be zero."
## [1] "W790RC1Q027SBEA has zero or negative values. Log series will be zero."
## [1] "VXX.Volume has zero or negative values. Log series will be zero."
## [1] "FYFSD has zero or negative values. Log series will be zero."
## [1] "FYFSGDA188S has zero or negative values. Log series will be zero."
## [1] "SOFR25 has zero or negative values. Log series will be zero."
## [1] "SOFR1 has zero or negative values. Log series will be zero."
## [1] "RPONTSYD has zero or negative values. Log series will be zero."
## [1] "BOPGTB has zero or negative values. Log series will be zero."
## [1] "EES.Volume has zero or negative values. Log series will be zero."
## [1] "VGSTX.Volume has zero or negative values. Log series will be zero."
## [1] "VFINX.Volume has zero or negative values. Log series will be zero."
## [1] "TMFGX.Volume has zero or negative values. Log series will be zero."
## [1] "FSMAX.Volume has zero or negative values. Log series will be zero."
## [1] "FXNAX.Volume has zero or negative values. Log series will be zero."
## [1] "HAINX.Volume has zero or negative values. Log series will be zero."
## [1] "HNACX.Volume has zero or negative values. Log series will be zero."
## [1] "VEIRX.Volume has zero or negative values. Log series will be zero."
## [1] "IVOO.Volume has zero or negative values. Log series will be zero."
## [1] "VO.Volume has zero or negative values. Log series will be zero."
## [1] "CZA.Volume has zero or negative values. Log series will be zero."
## [1] "SLY.Volume has zero or negative values. Log series will be zero."
## [1] "HYMB.Volume has zero or negative values. Log series will be zero."
## [1] "GOLD.Open has zero or negative values. Log series will be zero."
## [1] "GOLD.Volume has zero or negative values. Log series will be zero."
## [1] "BKR.Open has zero or negative values. Log series will be zero."
## [1] "BKR.Volume has zero or negative values. Log series will be zero."
## [1] "HAL.Open has zero or negative values. Log series will be zero."
## [1] "HAL.Volume has zero or negative values. Log series will be zero."
## [1] "IP.Open has zero or negative values. Log series will be zero."
## [1] "T.Open has zero or negative values. Log series will be zero."
## [1] "OPEARNINGSPERSHARE has zero or negative values. Log series will be zero."
## [1] "AREARNINGSPERSHARE has zero or negative values. Log series will be zero."
## [1] "OCCEquityVolume has zero or negative values. Log series will be zero."
## [1] "OCCNonEquityVolume has zero or negative values. Log series will be zero."
## [1] "BUSLOANS.minus.BUSLOANSNSA has zero or negative values. Log series will be zero."
## [1] "BUSLOANS.minus.BUSLOANSNSA.by.GDP has zero or negative values. Log series will be zero."
## [1] "EXPCH.minus.IMPCH has zero or negative values. Log series will be zero."
## [1] "EXPMX.minus.IMPMX has zero or negative values. Log series will be zero."
## [1] "SRPSABSNNCB.by.GDP has zero or negative values. Log series will be zero."
## [1] "DGS30TO10 has zero or negative values. Log series will be zero."
## [1] "DGS10TO1 has zero or negative values. Log series will be zero."
## [1] "DGS10TO2 has zero or negative values. Log series will be zero."
## [1] "DGS10TOTB3MS has zero or negative values. Log series will be zero."
## [1] "DGS10TODTB3 has zero or negative values. Log series will be zero."
## [1] "DCOILWTICO.by.PPIACO has zero or negative values. Log series will be zero."
## [1] "GSPC.DailySwing has zero or negative values. Log series will be zero."
df.data <- lst.df[[1]]
df.symbols <- lst.df[[2]]

Recession calculations

Summary calculations

These values are used below

Conclusion

In this worksheet a model predicting the onset of recession was built. From the model a trading rule was derived to allow backtesting. The model performed well and the trading rule backtesting showed that applying this in the post-WWII period would have resulted in an increase in returns. That is not too bad, but there are a few changes that would likely improve the model:

Market Conditions

#The model is predicting a `r paste(sprintf("%3.0f", tail(df.data$recession.initiation.smooth.avg,1)[[1]]*100), "%", sep="")` chance of recession in the next 12 months. :

#- P/E ratio of `r sprintf("%3.2f", tail(df.data$MULTPLSP500PERATIOMONTH,1))` compares to a historical mean value over the last decade of `r sprintf("%3.2f", df.data$MULTPLSP500PERATIOMONTH_Mean[1])`. Since 2008 recession P/E has only fallen below historical norm a few times. The current value is high, but well off the peaks. If earnings are +2-4% year-over-year then it is not unrealistic.

As of Feb 2020 we have entered a recession as defined by the NBER yet the market continues to rise.

P/E ratio of 25.78 compares to a historical mean value over the last decade of 18.69. Since 2008 recession P/E has only fallen below historical norm a few times. The current value is high, but well off the peaks. If earnings are +2-4% year-over-year then it is not unrealistic.

  • S&P 500 Volume, last updated on 2023-07-11, is flat over the last year and negative over the last month.

Unemployment

  • Headline unemployment (U-3) stands at 3.60% (last updated on 2023-06-01) which is near the 1-year average of 3.56% and rising with respect to the low in the last twelve months of 3.40%. Unlikely the rate will drop again.

  • Payrolls (BLS data, NSA) year-over-year stands at 2.58% which is above the 1-year average of 3.14% and falling with respect to the peak, in the last twelve months, of 4.23%.

  • Jobless claims (ICSA data) year-over-year stands at 13.99% (last updated on 2023-07-01) which is in-line with the 1-year average of -9.75% and below the peak, in the last twelve months, of 22.60%.
## Warning: Removed 1 rows containing missing values (geom_text).
## Warning: Removed 1 rows containing missing values (geom_hline).

Personal Income

  • Real personal income year over year growth stands at 0.84% (last updated on 2023-05-01). This is below the recent peak of 2.05%.

Yield Curve and Bond Market

  • The 10-year to 3-month yield stands at -1.26% (last updated on 2023-07-11). This is above the recent low of -1.73%. The trend is positive over the last year and negative over the last month.
## Warning: Removed 1 rows containing missing values (geom_text).
## Warning: Removed 1 rows containing missing values (geom_hline).

  • Auto sales flat?

Auxillary Series

I explored additional data series. The sections below have those data series along with comments.

Recent Highs

Print out the new 180 day high values

df.symbolsTrue <-
  df.symbols[df.symbols$'Max180' == TRUE, c("string.symbol", "string.description")]
df.symbolsTrue <-
  df.symbolsTrue[!(is.na(df.symbolsTrue$string.symbol)), ]
df.symbolsTrue <-
  df.symbolsTrue[!(df.symbolsTrue$string.symbol == 'USREC'), ]
#print(head(df.symbolsTrue,20))

kable(df.symbolsTrue, caption = "6-Month High") %>%
  kable_styling(bootstrap_options = c("striped", "hover"))  
6-Month High
string.symbol string.description
1 CPIAUCSL Consumer Price Index for All Urban Consumers: All Items
4 PCEPI Personal Consumption Expenditures: Chain-type Price Index
7 NPPTTL Total Nonfarm Private Payroll Employment (ADP)
8 U6RATE Total unemployed + margin + part-time U-6
9 PAYNSA All Employees: Total Nonfarm Payrolls (NSA)
10 TABSHNO Households and nonprofit organizations; total assets, Level
11 HNONWPDPI Household Net Worth, percent Dispsable Income
14 RSALES Real Retail Sales (DISCONTINUED)
15 W875RX1 Real personal income excluding current transfer receipts
16 RPI Real personal income
50 IMPCH U.S. Imports of Goods by Customs Basis from China (Monthly, NSA)
54 HSN1FNSA New One Family Houses Sold: United States (Monthly, NSA)
59 REALLNNSA Real Estate Loans, All Commercial Banks (Monthly, NSA)
60 REALLN Real Estate Loans, All Commercial Banks (Monthly, SA)
63 RREACBM027NBOG Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA)
64 RREACBM027SBOG Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
67 MORTGAGE30US 30-Year Fixed Rate Mortgage Average in the United States
68 CONSUMERNSA Consumer Loans, All Commercial Banks
71 DRCLACBS Delinquency Rate on Consumer Loans, All Commercial Banks, SA
73 SRPSABSNNCB Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA)
74 ASTLL All sectors; total loans; liability, Level (NSA)
75 FBDILNECA Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA)
76 ASOLAL All sectors; other loans and advances; liability, Level (NSA)
77 ASTMA All sectors; total mortgages; asset, Level (NSA)
78 ASHMA All sectors; home mortgages; asset, Level (NSA)
79 ASMRMA All sectors; multifamily residential mortgages; asset, Level (NSA)
80 ASCMA All sectors; commercial mortgages; asset, Level (NSA)
81 ASFMA All sectors; farm mortgages; asset, Level (NSA)
82 CCLBSHNO Households and nonprofit organizations; consumer credit; liability, Level (NSA)
83 FBDSILQ027S Domestic financial sectors debt securities; liability, Level (NSA)
84 FBLL Domestic financial sectors loans; liability, Level (NSA)
85 NCBDBIQ027S Nonfinancial corporate business; debt securities; liability, Level
90 DGS1 1-Year Treasury Constant Maturity Rate
92 TB3MS 3-Month Treasury Bill: Secondary Market Rate (Monthly)
97 NEWORDER Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft
109 GDP Gross Domestic Product
110 FNDEFX Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate)
111 FDEFX Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate)
112 GDPNOW Fed Atlanta GDPNow
113 GDPC1 Real Gross Domestic Product
114 GDPDEF Gross Domestic Product: Implicit Price Deflator
117 FEDFUNDS Effective Federal Funds Rate
118 GPDI Gross Private Domestic Investment
119 W790RC1Q027SBEA Net domestic investment: Private: Domestic busines
120 MZMV Velocity of MZM Money Stock
121 M1 M1 Money Stock
122 M2 M2 Money Stock
123 OPHNFB Nonfarm Business Sector: Real Output Per Hour of All Persons, SA
124 IPMAN Industrial Production: Manufacturing (NAICS)
126 GS5 5-Year Treasury Constant Maturity Rate
127 PSAVERT Personal Saving Rate
130 HOUST1F Privately Owned Housing Starts: 1-Unit Structures
131 GFDEBTN Federal Debt: Total Public Debt
132 HOUST Housing Starts: Total: New Privately Owned Housing Units Started, SA
133 HOUSTNSA Housing Starts: Total: New Privately Owned Housing Units Started, NSA
135 MSPUS Median Sales Price of Houses Sold for the United States (NSA)
137 DGORDER Manufacturers’ New Orders: Durable Goods (SA)
138 CSUSHPINSA S&P/Case-Shiller U.S. National Home Price Index (NSA)
139 GFDEGDQ188S Federal Debt: Total Public Debt as Percent of Gross Domestic Product
140 FYFSD Federal Surplus or Deficit
141 FYFSGDA188S Federal Surplus or Deficit [-] as Percent of Gross Domestic Product
146 OUTMS Manufacturing Sector: Real Output
147 MANEMP All Employees: Manufacturing
148 PRS30006163 Manufacturing Sector: Real Output Per Person
156 SOFR1 Secured Overnight Financing Rate: 1st Percentile
159 OBFR75 Overnight Bank Funding Rate: 75th Percentile
160 OBFR25 Overnight Bank Funding Rate: 25th Percentile
161 OBFR1 Overnight Bank Funding Rate: 1st Percentile
163 IOER Interest Rate on Excess Reserves
165 EXCSRESNW Excess Reserves of Depository Institutions
166 ECBASSETS Central Bank Assets for Euro Area (11-19 Countries)
167 EUNNGDP Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries)
168 CEU0600000007 Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing
169 CURRENCY Currency Component of M1 (Seasonally Adjusted)
170 WCURRNS Currency Component of M1
172 PRS88003193 Nonfinancial Corporations Sector: Unit Profits
175 POPTHM Population (U.S.)
176 POPTHM Population (U.S.)
177 CLF16OV Civilian Labor Force Level, SA
178 LNU01000000 Civilian Labor Force Level, NSA
184 TERMCBPER24NS Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan
185 A065RC1A027NBEA Personal income (NSA)
186 PI Personal income (SA)
187 PCE Personal Consumption Expenditures (SA)
188 A053RC1Q027SBEA National income: Corporate profits before tax (without IVA and CCAdj)
189 CPROFIT Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj)
226 ISMMANPMI Institute of Supply Managment PMI Composite Index
227 MULTPLSP500PERATIOMONTH S&P 500 TTM P/E
228 MULTPLSP500SALESQUARTER S&P 500 TTM Sales (Not Inflation Adjusted)
231 CHRISCMEHG1 Copper Futures, Continuous Contract #1 (HG1) (Front Month)
232 WWDIWLDISAIRGOODMTK1 Air transport, freight
234 PETA103600001M U.S. Total Gasoline Retail Sales by Refiners, Monthly
235 PETA123600001M U.S. Regular Gasoline Retail Sales by Refiners, Monthly
236 PETA143B00001M U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly
237 PETA133B00001M U.S. Premium Gasoline Bulk Sales (Volume) by Refiners, Monthly
241 BKRTotal Total Rig Count
242 BKRGas Gas Rig Count
243 BKROil Oil Rig Count
244 FARMINCOME Net Farm Income
245 OPEARNINGSPERSHARE Operating Earnings per Share
246 AREARNINGSPERSHARE As-Reported Earnings per Share
247 CASHDIVIDENDSPERSHR Cash Dividends per Share
248 SALESPERSHR Sales per Share
249 BOOKVALPERSHR Book value per Share
250 CAPEXPERSHR Cap ex per Share
251 PRICE Price
252 OPEARNINGSTTM TTM Operating Earnings
253 AREARNINGSTTM TTM Reported Earnings
254 FINRAMarginDebt Margin Debt
256 OCCEquityVolume Equity Options Volume
257 OCCNonEquityVolume Non-Equity Options Volume
269 W875RX1.by.GDP Real Personal Income Normalized by GDP
270 A065RC1A027NBEA.by.GDP Personal Income (NSA) Normalized by GDP
271 PI.by.GDP Personal Income (SA) Normalized by GDP
272 A053RC1Q027SBEA.by.GDP National income: Corporate profits before tax (without IVA and CCAdj) Normalized by GDP
273 CPROFIT.by.GDP National income: Corporate profits before tax (with IVA and CCAdj) Normalized by GDP
274 CONSUMERNSA.by.GDP Consumer Loans Not Seasonally Adjusted divided by GDP
275 RREACBM027NBOG.by.GDP Residental Real Estate Loans (Monthly, NSA) divided by GDP
276 RREACBM027SBOG.by.GDP Residental Real Estate Loans (Monthly, SA) divided by GDP
280 DGORDER.by.GDP Durable Goods (Monthly, NSA) divided by GDP
281 ASHMA.by.GDP Home Mortgages (Quarterly, NSA) divided by GDP
282 ASHMA.INTEREST Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
283 ASHMA.INTEREST.by.GDP Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP
284 CONSUMERNSA.INTEREST Consumer Loans (Not Seasonally Adjusted) Interest Burdens
285 CONSUMERNSA.INTEREST.by.GDP Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP
286 TOTLNNSA Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA)
287 TOTLNNSA.by.GDP Total Loans Not Seasonally Adjusted divided by GDP
291 EXCSRESNW.by.GDP Excess Reserves of Depository Institutions Divided by GDP
296 SRPSABSNNCB.by.GDP Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP
297 ASTLL.by.GDP All sectors; total loans; liability, Level (NSA) Divided by GDP
298 ASFMA.by.GDP All sectors; farm mortgages; asset, Level (NSA) Divided by GDP
299 ASFMA.by.ASTLL All sectors; total loans Divided by farm mortgages
300 ASFMA.INTEREST Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
301 ASFMA.INTEREST.by.GDP Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
302 FARMINCOME.by.GDP Farm Income (Annual, NSA) Divided by GDP
305 ECBASSETS.by.EUNNGDP Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP
315 U6toU3 U6RATE minums UNRATE
316 CHRISCMEHG1.by.PPIACO Copper, $/lb, Normalized by commodities producer price index
323 GDP.by.GDPDEF Nominal GDP Normalized by GDP def
335 MSPUS.times.HOUST New privately owned units start times median price
336 HOUST.div.POPTHM Housing starts divided by U.S. population
343 CPIAUCSL_Smooth Savitsky-Golay Smoothed (p=3, n=365) Consumer Price Index for All Urban Consumers: All Items
346 CPIAUCSL_Log Log of Consumer Price Index for All Urban Consumers: All Items
347 CPIAUCSL_mva365 Consumer Price Index for All Urban Consumers: All Items 365 Day MA
348 CPIAUCSL_mva200 Consumer Price Index for All Urban Consumers: All Items 200 Day MA
349 CPIAUCSL_mva050 Consumer Price Index for All Urban Consumers: All Items 50 Day MA
350 USREC_YoY NBER based Recession Indicators Year over Year
351 USREC_YoY4 NBER based Recession Indicators 4 Year over 4 Year
352 USREC_YoY5 NBER based Recession Indicators 5 Year over 5 Year
353 USREC_Smooth Savitsky-Golay Smoothed (p=3, n=365) NBER based Recession Indicators
354 USREC_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) NBER based Recession Indicators
355 USREC_SmoothDer Derivative of Smoothed NBER based Recession Indicators
356 USREC_Log Log of NBER based Recession Indicators
357 USREC_mva365 NBER based Recession Indicators 365 Day MA
358 USREC_mva200 NBER based Recession Indicators 200 Day MA
359 USREC_mva050 NBER based Recession Indicators 50 Day MA
363 UNRATE_Smooth Savitsky-Golay Smoothed (p=3, n=365) Civilian Unemployment Rate U-3
365 UNRATE_SmoothDer Derivative of Smoothed Civilian Unemployment Rate U-3
376 PCEPI_Log Log of Personal Consumption Expenditures: Chain-type Price Index
377 PCEPI_mva365 Personal Consumption Expenditures: Chain-type Price Index 365 Day MA
378 PCEPI_mva200 Personal Consumption Expenditures: Chain-type Price Index 200 Day MA
379 PCEPI_mva050 Personal Consumption Expenditures: Chain-type Price Index 50 Day MA
381 CCSA_YoY4 Continued Claims (Insured Unemployment) 4 Year over 4 Year
387 CCSA_mva365 Continued Claims (Insured Unemployment) 365 Day MA
388 CCSA_mva200 Continued Claims (Insured Unemployment) 200 Day MA
397 CCNSA_mva365 Continued Claims (Insured Unemployment, NSA) 365 Day MA
398 CCNSA_mva200 Continued Claims (Insured Unemployment, NSA) 200 Day MA
405 NPPTTL_SmoothDer Derivative of Smoothed Total Nonfarm Private Payroll Employment (ADP)
406 NPPTTL_Log Log of Total Nonfarm Private Payroll Employment (ADP)
407 NPPTTL_mva365 Total Nonfarm Private Payroll Employment (ADP) 365 Day MA
408 NPPTTL_mva200 Total Nonfarm Private Payroll Employment (ADP) 200 Day MA
409 NPPTTL_mva050 Total Nonfarm Private Payroll Employment (ADP) 50 Day MA
412 U6RATE_YoY5 Total unemployed + margin + part-time U-6 5 Year over 5 Year
413 U6RATE_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total unemployed + margin + part-time U-6
415 U6RATE_SmoothDer Derivative of Smoothed Total unemployed + margin + part-time U-6
416 U6RATE_Log Log of Total unemployed + margin + part-time U-6
418 U6RATE_mva200 Total unemployed + margin + part-time U-6 200 Day MA
419 U6RATE_mva050 Total unemployed + margin + part-time U-6 50 Day MA
423 PAYNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) All Employees: Total Nonfarm Payrolls (NSA)
425 PAYNSA_SmoothDer Derivative of Smoothed All Employees: Total Nonfarm Payrolls (NSA)
426 PAYNSA_Log Log of All Employees: Total Nonfarm Payrolls (NSA)
427 PAYNSA_mva365 All Employees: Total Nonfarm Payrolls (NSA) 365 Day MA
428 PAYNSA_mva200 All Employees: Total Nonfarm Payrolls (NSA) 200 Day MA
429 PAYNSA_mva050 All Employees: Total Nonfarm Payrolls (NSA) 50 Day MA
436 TABSHNO_Log Log of Households and nonprofit organizations; total assets, Level
437 TABSHNO_mva365 Households and nonprofit organizations; total assets, Level 365 Day MA
438 TABSHNO_mva200 Households and nonprofit organizations; total assets, Level 200 Day MA
439 TABSHNO_mva050 Households and nonprofit organizations; total assets, Level 50 Day MA
440 HNONWPDPI_YoY Household Net Worth, percent Dispsable Income Year over Year
442 HNONWPDPI_YoY5 Household Net Worth, percent Dispsable Income 5 Year over 5 Year
446 HNONWPDPI_Log Log of Household Net Worth, percent Dispsable Income
453 INDPRO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Industrial Production Index
455 INDPRO_SmoothDer Derivative of Smoothed Industrial Production Index
465 RRSFS_SmoothDer Derivative of Smoothed Real Retail and Food Services Sales
470 RSALES_YoY Real Retail Sales (DISCONTINUED) Year over Year
471 RSALES_YoY4 Real Retail Sales (DISCONTINUED) 4 Year over 4 Year
472 RSALES_YoY5 Real Retail Sales (DISCONTINUED) 5 Year over 5 Year
476 RSALES_Log Log of Real Retail Sales (DISCONTINUED)
477 RSALES_mva365 Real Retail Sales (DISCONTINUED) 365 Day MA
478 RSALES_mva200 Real Retail Sales (DISCONTINUED) 200 Day MA
479 RSALES_mva050 Real Retail Sales (DISCONTINUED) 50 Day MA
483 W875RX1_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real personal income excluding current transfer receipts
485 W875RX1_SmoothDer Derivative of Smoothed Real personal income excluding current transfer receipts
486 W875RX1_Log Log of Real personal income excluding current transfer receipts
487 W875RX1_mva365 Real personal income excluding current transfer receipts 365 Day MA
488 W875RX1_mva200 Real personal income excluding current transfer receipts 200 Day MA
489 W875RX1_mva050 Real personal income excluding current transfer receipts 50 Day MA
493 RPI_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real personal income
496 RPI_Log Log of Real personal income
497 RPI_mva365 Real personal income 365 Day MA
498 RPI_mva200 Real personal income 200 Day MA
499 RPI_mva050 Real personal income 50 Day MA
502 PCOPPUSDM_YoY5 Global price of Copper 5 Year over 5 Year
514 NOBL.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
524 NOBL.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
534 NOBL.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
537 NOBL.Low_mva365 365 Day MA
544 NOBL.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
546 NOBL.Close_Log Log of
554 NOBL.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
555 NOBL.Volume_SmoothDer Derivative of Smoothed
564 NOBL.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
566 NOBL.Adjusted_Log Log of
567 NOBL.Adjusted_mva365 365 Day MA
568 NOBL.Adjusted_mva200 200 Day MA
569 NOBL.Adjusted_mva050 50 Day MA
753 GSFTX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
754 GSFTX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
763 GSFTX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
764 GSFTX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
773 GSFTX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
774 GSFTX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
783 GSFTX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
784 GSFTX.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
790 GSFTX.Volume_YoY Year over Year
791 GSFTX.Volume_YoY4 4 Year over 4 Year
792 GSFTX.Volume_YoY5 5 Year over 5 Year
793 GSFTX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
794 GSFTX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
795 GSFTX.Volume_SmoothDer Derivative of Smoothed
796 GSFTX.Volume_Log Log of
797 GSFTX.Volume_mva365 365 Day MA
798 GSFTX.Volume_mva200 200 Day MA
799 GSFTX.Volume_mva050 50 Day MA
804 GSFTX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
807 GSFTX.Adjusted_mva365 365 Day MA
808 GSFTX.Adjusted_mva200 200 Day MA
809 GSFTX.Adjusted_mva050 50 Day MA
815 LFMIX.Open_SmoothDer Derivative of Smoothed
825 LFMIX.High_SmoothDer Derivative of Smoothed
835 LFMIX.Low_SmoothDer Derivative of Smoothed
845 LFMIX.Close_SmoothDer Derivative of Smoothed
850 LFMIX.Volume_YoY Year over Year
851 LFMIX.Volume_YoY4 4 Year over 4 Year
852 LFMIX.Volume_YoY5 5 Year over 5 Year
853 LFMIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
854 LFMIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
855 LFMIX.Volume_SmoothDer Derivative of Smoothed
856 LFMIX.Volume_Log Log of
857 LFMIX.Volume_mva365 365 Day MA
858 LFMIX.Volume_mva200 200 Day MA
859 LFMIX.Volume_mva050 50 Day MA
865 LFMIX.Adjusted_SmoothDer Derivative of Smoothed
875 LFMCX.Open_SmoothDer Derivative of Smoothed
885 LFMCX.High_SmoothDer Derivative of Smoothed
895 LFMCX.Low_SmoothDer Derivative of Smoothed
905 LFMCX.Close_SmoothDer Derivative of Smoothed
910 LFMCX.Volume_YoY Year over Year
911 LFMCX.Volume_YoY4 4 Year over 4 Year
912 LFMCX.Volume_YoY5 5 Year over 5 Year
913 LFMCX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
914 LFMCX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
915 LFMCX.Volume_SmoothDer Derivative of Smoothed
916 LFMCX.Volume_Log Log of
917 LFMCX.Volume_mva365 365 Day MA
918 LFMCX.Volume_mva200 200 Day MA
919 LFMCX.Volume_mva050 50 Day MA
925 LFMCX.Adjusted_SmoothDer Derivative of Smoothed
935 LFMAX.Open_SmoothDer Derivative of Smoothed
945 LFMAX.High_SmoothDer Derivative of Smoothed
955 LFMAX.Low_SmoothDer Derivative of Smoothed
965 LFMAX.Close_SmoothDer Derivative of Smoothed
970 LFMAX.Volume_YoY Year over Year
971 LFMAX.Volume_YoY4 4 Year over 4 Year
972 LFMAX.Volume_YoY5 5 Year over 5 Year
973 LFMAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
974 LFMAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
975 LFMAX.Volume_SmoothDer Derivative of Smoothed
976 LFMAX.Volume_Log Log of
977 LFMAX.Volume_mva365 365 Day MA
978 LFMAX.Volume_mva200 200 Day MA
979 LFMAX.Volume_mva050 50 Day MA
985 LFMAX.Adjusted_SmoothDer Derivative of Smoothed
995 LCSIX.Open_SmoothDer Derivative of Smoothed
1005 LCSIX.High_SmoothDer Derivative of Smoothed
1015 LCSIX.Low_SmoothDer Derivative of Smoothed
1025 LCSIX.Close_SmoothDer Derivative of Smoothed
1030 LCSIX.Volume_YoY Year over Year
1031 LCSIX.Volume_YoY4 4 Year over 4 Year
1032 LCSIX.Volume_YoY5 5 Year over 5 Year
1033 LCSIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1034 LCSIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1035 LCSIX.Volume_SmoothDer Derivative of Smoothed
1036 LCSIX.Volume_Log Log of
1037 LCSIX.Volume_mva365 365 Day MA
1038 LCSIX.Volume_mva200 200 Day MA
1039 LCSIX.Volume_mva050 50 Day MA
1095 BSV.Volume_SmoothDer Derivative of Smoothed
1108 BSV.Adjusted_mva200 200 Day MA
1150 VBIRX.Volume_YoY Year over Year
1151 VBIRX.Volume_YoY4 4 Year over 4 Year
1152 VBIRX.Volume_YoY5 5 Year over 5 Year
1153 VBIRX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1154 VBIRX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1155 VBIRX.Volume_SmoothDer Derivative of Smoothed
1156 VBIRX.Volume_Log Log of
1157 VBIRX.Volume_mva365 365 Day MA
1158 VBIRX.Volume_mva200 200 Day MA
1159 VBIRX.Volume_mva050 50 Day MA
1168 VBIRX.Adjusted_mva200 200 Day MA
1270 VFSUX.Volume_YoY Year over Year
1271 VFSUX.Volume_YoY4 4 Year over 4 Year
1272 VFSUX.Volume_YoY5 5 Year over 5 Year
1273 VFSUX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1274 VFSUX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1275 VFSUX.Volume_SmoothDer Derivative of Smoothed
1276 VFSUX.Volume_Log Log of
1277 VFSUX.Volume_mva365 365 Day MA
1278 VFSUX.Volume_mva200 200 Day MA
1279 VFSUX.Volume_mva050 50 Day MA
1288 VFSUX.Adjusted_mva200 200 Day MA
1330 LTUIX.Volume_YoY Year over Year
1331 LTUIX.Volume_YoY4 4 Year over 4 Year
1332 LTUIX.Volume_YoY5 5 Year over 5 Year
1333 LTUIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1334 LTUIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1335 LTUIX.Volume_SmoothDer Derivative of Smoothed
1336 LTUIX.Volume_Log Log of
1337 LTUIX.Volume_mva365 365 Day MA
1338 LTUIX.Volume_mva200 200 Day MA
1339 LTUIX.Volume_mva050 50 Day MA
1390 PTTPX.Volume_YoY Year over Year
1391 PTTPX.Volume_YoY4 4 Year over 4 Year
1392 PTTPX.Volume_YoY5 5 Year over 5 Year
1393 PTTPX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1394 PTTPX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1395 PTTPX.Volume_SmoothDer Derivative of Smoothed
1396 PTTPX.Volume_Log Log of
1397 PTTPX.Volume_mva365 365 Day MA
1398 PTTPX.Volume_mva200 200 Day MA
1399 PTTPX.Volume_mva050 50 Day MA
1450 NERYX.Volume_YoY Year over Year
1451 NERYX.Volume_YoY4 4 Year over 4 Year
1452 NERYX.Volume_YoY5 5 Year over 5 Year
1453 NERYX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1454 NERYX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1455 NERYX.Volume_SmoothDer Derivative of Smoothed
1456 NERYX.Volume_Log Log of
1457 NERYX.Volume_mva365 365 Day MA
1458 NERYX.Volume_mva200 200 Day MA
1459 NERYX.Volume_mva050 50 Day MA
1510 STIGX.Volume_YoY Year over Year
1511 STIGX.Volume_YoY4 4 Year over 4 Year
1512 STIGX.Volume_YoY5 5 Year over 5 Year
1513 STIGX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1514 STIGX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1515 STIGX.Volume_SmoothDer Derivative of Smoothed
1516 STIGX.Volume_Log Log of
1517 STIGX.Volume_mva365 365 Day MA
1518 STIGX.Volume_mva200 200 Day MA
1519 STIGX.Volume_mva050 50 Day MA
1570 HLGAX.Volume_YoY Year over Year
1571 HLGAX.Volume_YoY4 4 Year over 4 Year
1572 HLGAX.Volume_YoY5 5 Year over 5 Year
1573 HLGAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1574 HLGAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1575 HLGAX.Volume_SmoothDer Derivative of Smoothed
1576 HLGAX.Volume_Log Log of
1577 HLGAX.Volume_mva365 365 Day MA
1578 HLGAX.Volume_mva200 200 Day MA
1579 HLGAX.Volume_mva050 50 Day MA
1630 FTRGX.Volume_YoY Year over Year
1631 FTRGX.Volume_YoY4 4 Year over 4 Year
1632 FTRGX.Volume_YoY5 5 Year over 5 Year
1633 FTRGX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1634 FTRGX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1635 FTRGX.Volume_SmoothDer Derivative of Smoothed
1636 FTRGX.Volume_Log Log of
1637 FTRGX.Volume_mva365 365 Day MA
1638 FTRGX.Volume_mva200 200 Day MA
1639 FTRGX.Volume_mva050 50 Day MA
1690 THIIX.Volume_YoY Year over Year
1691 THIIX.Volume_YoY4 4 Year over 4 Year
1692 THIIX.Volume_YoY5 5 Year over 5 Year
1693 THIIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1694 THIIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1695 THIIX.Volume_SmoothDer Derivative of Smoothed
1696 THIIX.Volume_Log Log of
1697 THIIX.Volume_mva365 365 Day MA
1698 THIIX.Volume_mva200 200 Day MA
1699 THIIX.Volume_mva050 50 Day MA
1708 THIIX.Adjusted_mva200 200 Day MA
1750 PTTRX.Volume_YoY Year over Year
1751 PTTRX.Volume_YoY4 4 Year over 4 Year
1752 PTTRX.Volume_YoY5 5 Year over 5 Year
1753 PTTRX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1754 PTTRX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1755 PTTRX.Volume_SmoothDer Derivative of Smoothed
1756 PTTRX.Volume_Log Log of
1757 PTTRX.Volume_mva365 365 Day MA
1758 PTTRX.Volume_mva200 200 Day MA
1759 PTTRX.Volume_mva050 50 Day MA
1775 BFIGX.Open_SmoothDer Derivative of Smoothed
1785 BFIGX.High_SmoothDer Derivative of Smoothed
1795 BFIGX.Low_SmoothDer Derivative of Smoothed
1805 BFIGX.Close_SmoothDer Derivative of Smoothed
1810 BFIGX.Volume_YoY Year over Year
1811 BFIGX.Volume_YoY4 4 Year over 4 Year
1812 BFIGX.Volume_YoY5 5 Year over 5 Year
1813 BFIGX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1814 BFIGX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1815 BFIGX.Volume_SmoothDer Derivative of Smoothed
1816 BFIGX.Volume_Log Log of
1817 BFIGX.Volume_mva365 365 Day MA
1818 BFIGX.Volume_mva200 200 Day MA
1819 BFIGX.Volume_mva050 50 Day MA
1833 VTWO.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1843 VTWO.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1853 VTWO.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1863 VTWO.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1883 VTWO.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1888 VTWO.Adjusted_mva200 200 Day MA
1898 EIFAX.Open_mva200 200 Day MA
1908 EIFAX.High_mva200 200 Day MA
1918 EIFAX.Low_mva200 200 Day MA
1928 EIFAX.Close_mva200 200 Day MA
1930 EIFAX.Volume_YoY Year over Year
1931 EIFAX.Volume_YoY4 4 Year over 4 Year
1932 EIFAX.Volume_YoY5 5 Year over 5 Year
1933 EIFAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1934 EIFAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1935 EIFAX.Volume_SmoothDer Derivative of Smoothed
1936 EIFAX.Volume_Log Log of
1937 EIFAX.Volume_mva365 365 Day MA
1938 EIFAX.Volume_mva200 200 Day MA
1939 EIFAX.Volume_mva050 50 Day MA
1944 EIFAX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1946 EIFAX.Adjusted_Log Log of
1947 EIFAX.Adjusted_mva365 365 Day MA
1948 EIFAX.Adjusted_mva200 200 Day MA
1949 EIFAX.Adjusted_mva050 50 Day MA
1958 ASDAX.Open_mva200 200 Day MA
1968 ASDAX.High_mva200 200 Day MA
1978 ASDAX.Low_mva200 200 Day MA
1988 ASDAX.Close_mva200 200 Day MA
1990 ASDAX.Volume_YoY Year over Year
1991 ASDAX.Volume_YoY4 4 Year over 4 Year
1992 ASDAX.Volume_YoY5 5 Year over 5 Year
1993 ASDAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1994 ASDAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1995 ASDAX.Volume_SmoothDer Derivative of Smoothed
1996 ASDAX.Volume_Log Log of
1997 ASDAX.Volume_mva365 365 Day MA
1998 ASDAX.Volume_mva200 200 Day MA
1999 ASDAX.Volume_mva050 50 Day MA
2007 ASDAX.Adjusted_mva365 365 Day MA
2008 ASDAX.Adjusted_mva200 200 Day MA
2010 TRBUX.Open_YoY Year over Year
2012 TRBUX.Open_YoY5 5 Year over 5 Year
2015 TRBUX.Open_SmoothDer Derivative of Smoothed
2016 TRBUX.Open_Log Log of
2018 TRBUX.Open_mva200 200 Day MA
2019 TRBUX.Open_mva050 50 Day MA
2020 TRBUX.High_YoY Year over Year
2022 TRBUX.High_YoY5 5 Year over 5 Year
2025 TRBUX.High_SmoothDer Derivative of Smoothed
2026 TRBUX.High_Log Log of
2028 TRBUX.High_mva200 200 Day MA
2029 TRBUX.High_mva050 50 Day MA
2030 TRBUX.Low_YoY Year over Year
2032 TRBUX.Low_YoY5 5 Year over 5 Year
2035 TRBUX.Low_SmoothDer Derivative of Smoothed
2036 TRBUX.Low_Log Log of
2038 TRBUX.Low_mva200 200 Day MA
2039 TRBUX.Low_mva050 50 Day MA
2040 TRBUX.Close_YoY Year over Year
2042 TRBUX.Close_YoY5 5 Year over 5 Year
2045 TRBUX.Close_SmoothDer Derivative of Smoothed
2046 TRBUX.Close_Log Log of
2048 TRBUX.Close_mva200 200 Day MA
2049 TRBUX.Close_mva050 50 Day MA
2050 TRBUX.Volume_YoY Year over Year
2051 TRBUX.Volume_YoY4 4 Year over 4 Year
2052 TRBUX.Volume_YoY5 5 Year over 5 Year
2053 TRBUX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2054 TRBUX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2055 TRBUX.Volume_SmoothDer Derivative of Smoothed
2056 TRBUX.Volume_Log Log of
2057 TRBUX.Volume_mva365 365 Day MA
2058 TRBUX.Volume_mva200 200 Day MA
2059 TRBUX.Volume_mva050 50 Day MA
2066 TRBUX.Adjusted_Log Log of
2067 TRBUX.Adjusted_mva365 365 Day MA
2068 TRBUX.Adjusted_mva200 200 Day MA
2069 TRBUX.Adjusted_mva050 50 Day MA
2110 PRVIX.Volume_YoY Year over Year
2111 PRVIX.Volume_YoY4 4 Year over 4 Year
2112 PRVIX.Volume_YoY5 5 Year over 5 Year
2113 PRVIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2114 PRVIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2115 PRVIX.Volume_SmoothDer Derivative of Smoothed
2116 PRVIX.Volume_Log Log of
2117 PRVIX.Volume_mva365 365 Day MA
2118 PRVIX.Volume_mva200 200 Day MA
2119 PRVIX.Volume_mva050 50 Day MA
2133 PRWCX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2134 PRWCX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2135 PRWCX.Open_SmoothDer Derivative of Smoothed
2139 PRWCX.Open_mva050 50 Day MA
2143 PRWCX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2144 PRWCX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2145 PRWCX.High_SmoothDer Derivative of Smoothed
2149 PRWCX.High_mva050 50 Day MA
2153 PRWCX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2154 PRWCX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2155 PRWCX.Low_SmoothDer Derivative of Smoothed
2159 PRWCX.Low_mva050 50 Day MA
2163 PRWCX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2164 PRWCX.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2165 PRWCX.Close_SmoothDer Derivative of Smoothed
2169 PRWCX.Close_mva050 50 Day MA
2170 PRWCX.Volume_YoY Year over Year
2171 PRWCX.Volume_YoY4 4 Year over 4 Year
2172 PRWCX.Volume_YoY5 5 Year over 5 Year
2173 PRWCX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2174 PRWCX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2175 PRWCX.Volume_SmoothDer Derivative of Smoothed
2176 PRWCX.Volume_Log Log of
2177 PRWCX.Volume_mva365 365 Day MA
2178 PRWCX.Volume_mva200 200 Day MA
2179 PRWCX.Volume_mva050 50 Day MA
2183 PRWCX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2184 PRWCX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2187 PRWCX.Adjusted_mva365 365 Day MA
2188 PRWCX.Adjusted_mva200 200 Day MA
2189 PRWCX.Adjusted_mva050 50 Day MA
2193 ADOZX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2203 ADOZX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2213 ADOZX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2223 ADOZX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2230 ADOZX.Volume_YoY Year over Year
2231 ADOZX.Volume_YoY4 4 Year over 4 Year
2232 ADOZX.Volume_YoY5 5 Year over 5 Year
2233 ADOZX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2234 ADOZX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2235 ADOZX.Volume_SmoothDer Derivative of Smoothed
2236 ADOZX.Volume_Log Log of
2237 ADOZX.Volume_mva365 365 Day MA
2238 ADOZX.Volume_mva200 200 Day MA
2239 ADOZX.Volume_mva050 50 Day MA
2243 ADOZX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2290 MERFX.Volume_YoY Year over Year
2291 MERFX.Volume_YoY4 4 Year over 4 Year
2292 MERFX.Volume_YoY5 5 Year over 5 Year
2293 MERFX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2294 MERFX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2295 MERFX.Volume_SmoothDer Derivative of Smoothed
2296 MERFX.Volume_Log Log of
2297 MERFX.Volume_mva365 365 Day MA
2298 MERFX.Volume_mva200 200 Day MA
2299 MERFX.Volume_mva050 50 Day MA
2307 MERFX.Adjusted_mva365 365 Day MA
2313 CMNIX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2314 CMNIX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2317 CMNIX.Open_mva365 365 Day MA
2318 CMNIX.Open_mva200 200 Day MA
2319 CMNIX.Open_mva050 50 Day MA
2323 CMNIX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2324 CMNIX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2327 CMNIX.High_mva365 365 Day MA
2328 CMNIX.High_mva200 200 Day MA
2329 CMNIX.High_mva050 50 Day MA
2333 CMNIX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2334 CMNIX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2337 CMNIX.Low_mva365 365 Day MA
2338 CMNIX.Low_mva200 200 Day MA
2339 CMNIX.Low_mva050 50 Day MA
2343 CMNIX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2344 CMNIX.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2347 CMNIX.Close_mva365 365 Day MA
2348 CMNIX.Close_mva200 200 Day MA
2349 CMNIX.Close_mva050 50 Day MA
2350 CMNIX.Volume_YoY Year over Year
2351 CMNIX.Volume_YoY4 4 Year over 4 Year
2352 CMNIX.Volume_YoY5 5 Year over 5 Year
2353 CMNIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2354 CMNIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2355 CMNIX.Volume_SmoothDer Derivative of Smoothed
2356 CMNIX.Volume_Log Log of
2357 CMNIX.Volume_mva365 365 Day MA
2358 CMNIX.Volume_mva200 200 Day MA
2359 CMNIX.Volume_mva050 50 Day MA
2363 CMNIX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2364 CMNIX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2367 CMNIX.Adjusted_mva365 365 Day MA
2368 CMNIX.Adjusted_mva200 200 Day MA
2369 CMNIX.Adjusted_mva050 50 Day MA
2373 CIHEX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2375 CIHEX.Open_SmoothDer Derivative of Smoothed
2378 CIHEX.Open_mva200 200 Day MA
2379 CIHEX.Open_mva050 50 Day MA
2383 CIHEX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2385 CIHEX.High_SmoothDer Derivative of Smoothed
2388 CIHEX.High_mva200 200 Day MA
2389 CIHEX.High_mva050 50 Day MA
2393 CIHEX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2395 CIHEX.Low_SmoothDer Derivative of Smoothed
2398 CIHEX.Low_mva200 200 Day MA
2399 CIHEX.Low_mva050 50 Day MA
2403 CIHEX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2405 CIHEX.Close_SmoothDer Derivative of Smoothed
2408 CIHEX.Close_mva200 200 Day MA
2409 CIHEX.Close_mva050 50 Day MA
2410 CIHEX.Volume_YoY Year over Year
2411 CIHEX.Volume_YoY4 4 Year over 4 Year
2412 CIHEX.Volume_YoY5 5 Year over 5 Year
2413 CIHEX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2414 CIHEX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2415 CIHEX.Volume_SmoothDer Derivative of Smoothed
2416 CIHEX.Volume_Log Log of
2417 CIHEX.Volume_mva365 365 Day MA
2418 CIHEX.Volume_mva200 200 Day MA
2419 CIHEX.Volume_mva050 50 Day MA
2423 CIHEX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2425 CIHEX.Adjusted_SmoothDer Derivative of Smoothed
2427 CIHEX.Adjusted_mva365 365 Day MA
2428 CIHEX.Adjusted_mva200 200 Day MA
2429 CIHEX.Adjusted_mva050 50 Day MA
2433 IMPCH_Smooth Savitsky-Golay Smoothed (p=3, n=365) U.S. Imports of Goods by Customs Basis from China (Monthly, NSA)
2435 IMPCH_SmoothDer Derivative of Smoothed U.S. Imports of Goods by Customs Basis from China (Monthly, NSA)
2436 IMPCH_Log Log of U.S. Imports of Goods by Customs Basis from China (Monthly, NSA)
2453 IMPMX_Smooth Savitsky-Golay Smoothed (p=3, n=365) U.S. Imports of Goods by Customs Basis from Mexico (Monthly, NSA)
2455 IMPMX_SmoothDer Derivative of Smoothed U.S. Imports of Goods by Customs Basis from Mexico (Monthly, NSA)
2457 IMPMX_mva365 U.S. Imports of Goods by Customs Basis from Mexico (Monthly, NSA) 365 Day MA
2458 IMPMX_mva200 U.S. Imports of Goods by Customs Basis from Mexico (Monthly, NSA) 200 Day MA
2459 IMPMX_mva050 U.S. Imports of Goods by Customs Basis from Mexico (Monthly, NSA) 50 Day MA
2465 EXPMX_SmoothDer Derivative of Smoothed U.S. Exports of Goods by F.A.S. Basis to Mexico (Monthly, NSA)
2472 HSN1FNSA_YoY5 New One Family Houses Sold: United States (Monthly, NSA) 5 Year over 5 Year
2476 HSN1FNSA_Log Log of New One Family Houses Sold: United States (Monthly, NSA)
2477 HSN1FNSA_mva365 New One Family Houses Sold: United States (Monthly, NSA) 365 Day MA
2478 HSN1FNSA_mva200 New One Family Houses Sold: United States (Monthly, NSA) 200 Day MA
2479 HSN1FNSA_mva050 New One Family Houses Sold: United States (Monthly, NSA) 50 Day MA
2485 HNFSUSNSA_SmoothDer Derivative of Smoothed New One Family Houses for Sale in the United States (Monthly, NSA)
2497 BUSLOANS_mva365 Commercial and Industrial Loans, All Commercial Banks (Monthly, SA) 365 Day MA
2507 TOTCI_mva365 Commercial and Industrial Loans, All Commercial Banks (Weekly, SA) 365 Day MA
2517 BUSLOANSNSA_mva365 Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA) 365 Day MA
2526 REALLNNSA_Log Log of Real Estate Loans, All Commercial Banks (Monthly, NSA)
2527 REALLNNSA_mva365 Real Estate Loans, All Commercial Banks (Monthly, NSA) 365 Day MA
2528 REALLNNSA_mva200 Real Estate Loans, All Commercial Banks (Monthly, NSA) 200 Day MA
2529 REALLNNSA_mva050 Real Estate Loans, All Commercial Banks (Monthly, NSA) 50 Day MA
2536 REALLN_Log Log of Real Estate Loans, All Commercial Banks (Monthly, SA)
2537 REALLN_mva365 Real Estate Loans, All Commercial Banks (Monthly, SA) 365 Day MA
2538 REALLN_mva200 Real Estate Loans, All Commercial Banks (Monthly, SA) 200 Day MA
2539 REALLN_mva050 Real Estate Loans, All Commercial Banks (Monthly, SA) 50 Day MA
2547 RELACBW027NBOG_mva365 Real Estate Loans, All Commercial Banks (Weekly, NSA) 365 Day MA
2548 RELACBW027NBOG_mva200 Real Estate Loans, All Commercial Banks (Weekly, NSA) 200 Day MA
2549 RELACBW027NBOG_mva050 Real Estate Loans, All Commercial Banks (Weekly, NSA) 50 Day MA
2557 RELACBW027SBOG_mva365 Real Estate Loans, All Commercial Banks (Weekly, SA) 365 Day MA
2558 RELACBW027SBOG_mva200 Real Estate Loans, All Commercial Banks (Weekly, SA) 200 Day MA
2563 RREACBM027NBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA)
2566 RREACBM027NBOG_Log Log of Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA)
2567 RREACBM027NBOG_mva365 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA) 365 Day MA
2568 RREACBM027NBOG_mva200 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA) 200 Day MA
2569 RREACBM027NBOG_mva050 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA) 50 Day MA
2576 RREACBM027SBOG_Log Log of Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
2577 RREACBM027SBOG_mva365 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA) 365 Day MA
2578 RREACBM027SBOG_mva200 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA) 200 Day MA
2579 RREACBM027SBOG_mva050 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA) 50 Day MA
2587 RREACBW027SBOG_mva365 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA) 365 Day MA
2588 RREACBW027SBOG_mva200 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA) 200 Day MA
2593 RREACBW027NBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA)
2597 RREACBW027NBOG_mva365 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA) 365 Day MA
2598 RREACBW027NBOG_mva200 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA) 200 Day MA
2603 MORTGAGE30US_Smooth Savitsky-Golay Smoothed (p=3, n=365) 30-Year Fixed Rate Mortgage Average in the United States
2605 MORTGAGE30US_SmoothDer Derivative of Smoothed 30-Year Fixed Rate Mortgage Average in the United States
2606 MORTGAGE30US_Log Log of 30-Year Fixed Rate Mortgage Average in the United States
2607 MORTGAGE30US_mva365 30-Year Fixed Rate Mortgage Average in the United States 365 Day MA
2609 MORTGAGE30US_mva050 30-Year Fixed Rate Mortgage Average in the United States 50 Day MA
2613 CONSUMERNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Consumer Loans, All Commercial Banks
2616 CONSUMERNSA_Log Log of Consumer Loans, All Commercial Banks
2617 CONSUMERNSA_mva365 Consumer Loans, All Commercial Banks 365 Day MA
2618 CONSUMERNSA_mva200 Consumer Loans, All Commercial Banks 200 Day MA
2619 CONSUMERNSA_mva050 Consumer Loans, All Commercial Banks 50 Day MA
2627 TOTLLNSA_mva365 Loans and Leases in Bank Credit, All Commercial Banks 365 Day MA
2628 TOTLLNSA_mva200 Loans and Leases in Bank Credit, All Commercial Banks 200 Day MA
2629 TOTLLNSA_mva050 Loans and Leases in Bank Credit, All Commercial Banks 50 Day MA
2635 DPSACBW027SBOG_SmoothDer Derivative of Smoothed Deposits, All Commercial Banks
2641 DRCLACBS_YoY4 Delinquency Rate on Consumer Loans, All Commercial Banks, SA 4 Year over 4 Year
2646 DRCLACBS_Log Log of Delinquency Rate on Consumer Loans, All Commercial Banks, SA
2647 DRCLACBS_mva365 Delinquency Rate on Consumer Loans, All Commercial Banks, SA 365 Day MA
2648 DRCLACBS_mva200 Delinquency Rate on Consumer Loans, All Commercial Banks, SA 200 Day MA
2649 DRCLACBS_mva050 Delinquency Rate on Consumer Loans, All Commercial Banks, SA 50 Day MA
2657 TOTCINSA_mva365 Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA) 365 Day MA
2666 SRPSABSNNCB_Log Log of Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA)
2667 SRPSABSNNCB_mva365 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 365 Day MA
2668 SRPSABSNNCB_mva200 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 200 Day MA
2669 SRPSABSNNCB_mva050 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 50 Day MA
2676 ASTLL_Log Log of All sectors; total loans; liability, Level (NSA)
2677 ASTLL_mva365 All sectors; total loans; liability, Level (NSA) 365 Day MA
2678 ASTLL_mva200 All sectors; total loans; liability, Level (NSA) 200 Day MA
2679 ASTLL_mva050 All sectors; total loans; liability, Level (NSA) 50 Day MA
2683 FBDILNECA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA)
2686 FBDILNECA_Log Log of Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA)
2687 FBDILNECA_mva365 Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA) 365 Day MA
2688 FBDILNECA_mva200 Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA) 200 Day MA
2689 FBDILNECA_mva050 Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA) 50 Day MA
2691 ASOLAL_YoY4 All sectors; other loans and advances; liability, Level (NSA) 4 Year over 4 Year
2696 ASOLAL_Log Log of All sectors; other loans and advances; liability, Level (NSA)
2697 ASOLAL_mva365 All sectors; other loans and advances; liability, Level (NSA) 365 Day MA
2698 ASOLAL_mva200 All sectors; other loans and advances; liability, Level (NSA) 200 Day MA
2699 ASOLAL_mva050 All sectors; other loans and advances; liability, Level (NSA) 50 Day MA
2703 ASTMA_Smooth Savitsky-Golay Smoothed (p=3, n=365) All sectors; total mortgages; asset, Level (NSA)
2706 ASTMA_Log Log of All sectors; total mortgages; asset, Level (NSA)
2707 ASTMA_mva365 All sectors; total mortgages; asset, Level (NSA) 365 Day MA
2708 ASTMA_mva200 All sectors; total mortgages; asset, Level (NSA) 200 Day MA
2709 ASTMA_mva050 All sectors; total mortgages; asset, Level (NSA) 50 Day MA
2713 ASHMA_Smooth Savitsky-Golay Smoothed (p=3, n=365) All sectors; home mortgages; asset, Level (NSA)
2716 ASHMA_Log Log of All sectors; home mortgages; asset, Level (NSA)
2717 ASHMA_mva365 All sectors; home mortgages; asset, Level (NSA) 365 Day MA
2718 ASHMA_mva200 All sectors; home mortgages; asset, Level (NSA) 200 Day MA
2719 ASHMA_mva050 All sectors; home mortgages; asset, Level (NSA) 50 Day MA
2723 ASMRMA_Smooth Savitsky-Golay Smoothed (p=3, n=365) All sectors; multifamily residential mortgages; asset, Level (NSA)
2726 ASMRMA_Log Log of All sectors; multifamily residential mortgages; asset, Level (NSA)
2727 ASMRMA_mva365 All sectors; multifamily residential mortgages; asset, Level (NSA) 365 Day MA
2728 ASMRMA_mva200 All sectors; multifamily residential mortgages; asset, Level (NSA) 200 Day MA
2729 ASMRMA_mva050 All sectors; multifamily residential mortgages; asset, Level (NSA) 50 Day MA
2736 ASCMA_Log Log of All sectors; commercial mortgages; asset, Level (NSA)
2737 ASCMA_mva365 All sectors; commercial mortgages; asset, Level (NSA) 365 Day MA
2738 ASCMA_mva200 All sectors; commercial mortgages; asset, Level (NSA) 200 Day MA
2739 ASCMA_mva050 All sectors; commercial mortgages; asset, Level (NSA) 50 Day MA
2746 ASFMA_Log Log of All sectors; farm mortgages; asset, Level (NSA)
2747 ASFMA_mva365 All sectors; farm mortgages; asset, Level (NSA) 365 Day MA
2748 ASFMA_mva200 All sectors; farm mortgages; asset, Level (NSA) 200 Day MA
2749 ASFMA_mva050 All sectors; farm mortgages; asset, Level (NSA) 50 Day MA
2753 CCLBSHNO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Households and nonprofit organizations; consumer credit; liability, Level (NSA)
2756 CCLBSHNO_Log Log of Households and nonprofit organizations; consumer credit; liability, Level (NSA)
2757 CCLBSHNO_mva365 Households and nonprofit organizations; consumer credit; liability, Level (NSA) 365 Day MA
2766 FBDSILQ027S_Log Log of Domestic financial sectors debt securities; liability, Level (NSA)
2767 FBDSILQ027S_mva365 Domestic financial sectors debt securities; liability, Level (NSA) 365 Day MA
2768 FBDSILQ027S_mva200 Domestic financial sectors debt securities; liability, Level (NSA) 200 Day MA
2769 FBDSILQ027S_mva050 Domestic financial sectors debt securities; liability, Level (NSA) 50 Day MA
2776 FBLL_Log Log of Domestic financial sectors loans; liability, Level (NSA)
2777 FBLL_mva365 Domestic financial sectors loans; liability, Level (NSA) 365 Day MA
2778 FBLL_mva200 Domestic financial sectors loans; liability, Level (NSA) 200 Day MA
2779 FBLL_mva050 Domestic financial sectors loans; liability, Level (NSA) 50 Day MA
2786 NCBDBIQ027S_Log Log of Nonfinancial corporate business; debt securities; liability, Level
2787 NCBDBIQ027S_mva365 Nonfinancial corporate business; debt securities; liability, Level 365 Day MA
2788 NCBDBIQ027S_mva200 Nonfinancial corporate business; debt securities; liability, Level 200 Day MA
2789 NCBDBIQ027S_mva050 Nonfinancial corporate business; debt securities; liability, Level 50 Day MA
2793 DGS10_Smooth Savitsky-Golay Smoothed (p=3, n=365) 10-Year Treasury Constant Maturity Rate
2795 DGS10_SmoothDer Derivative of Smoothed 10-Year Treasury Constant Maturity Rate
2797 DGS10_mva365 10-Year Treasury Constant Maturity Rate 365 Day MA
2799 DGS10_mva050 10-Year Treasury Constant Maturity Rate 50 Day MA
2803 TNX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2805 TNX.Open_SmoothDer Derivative of Smoothed
2807 TNX.Open_mva365 365 Day MA
2809 TNX.Open_mva050 50 Day MA
2813 TNX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2815 TNX.High_SmoothDer Derivative of Smoothed
2817 TNX.High_mva365 365 Day MA
2819 TNX.High_mva050 50 Day MA
2823 TNX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2825 TNX.Low_SmoothDer Derivative of Smoothed
2827 TNX.Low_mva365 365 Day MA
2829 TNX.Low_mva050 50 Day MA
2833 TNX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2835 TNX.Close_SmoothDer Derivative of Smoothed
2837 TNX.Close_mva365 365 Day MA
2839 TNX.Close_mva050 50 Day MA
2840 TNX.Volume_YoY Year over Year
2841 TNX.Volume_YoY4 4 Year over 4 Year
2842 TNX.Volume_YoY5 5 Year over 5 Year
2843 TNX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2844 TNX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2845 TNX.Volume_SmoothDer Derivative of Smoothed
2846 TNX.Volume_Log Log of
2847 TNX.Volume_mva365 365 Day MA
2848 TNX.Volume_mva200 200 Day MA
2849 TNX.Volume_mva050 50 Day MA
2853 TNX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2855 TNX.Adjusted_SmoothDer Derivative of Smoothed
2857 TNX.Adjusted_mva365 365 Day MA
2859 TNX.Adjusted_mva050 50 Day MA
2865 CLF.Open_SmoothDer Derivative of Smoothed
2866 CLF.Open_Log Log of
2875 CLF.High_SmoothDer Derivative of Smoothed
2885 CLF.Low_SmoothDer Derivative of Smoothed
2886 CLF.Low_Log Log of
2895 CLF.Close_SmoothDer Derivative of Smoothed
2896 CLF.Close_Log Log of
2903 CLF.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2906 CLF.Volume_Log Log of
2908 CLF.Volume_mva200 200 Day MA
2909 CLF.Volume_mva050 50 Day MA
2915 CLF.Adjusted_SmoothDer Derivative of Smoothed
2916 CLF.Adjusted_Log Log of
2923 DGS30_Smooth Savitsky-Golay Smoothed (p=3, n=365) 10-Year Treasury Constant Maturity Rate
2925 DGS30_SmoothDer Derivative of Smoothed 10-Year Treasury Constant Maturity Rate
2927 DGS30_mva365 10-Year Treasury Constant Maturity Rate 365 Day MA
2929 DGS30_mva050 10-Year Treasury Constant Maturity Rate 50 Day MA
2933 DGS1_Smooth Savitsky-Golay Smoothed (p=3, n=365) 1-Year Treasury Constant Maturity Rate
2934 DGS1_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) 1-Year Treasury Constant Maturity Rate
2936 DGS1_Log Log of 1-Year Treasury Constant Maturity Rate
2937 DGS1_mva365 1-Year Treasury Constant Maturity Rate 365 Day MA
2938 DGS1_mva200 1-Year Treasury Constant Maturity Rate 200 Day MA
2939 DGS1_mva050 1-Year Treasury Constant Maturity Rate 50 Day MA
2943 DGS2_Smooth Savitsky-Golay Smoothed (p=3, n=365) 2-Year Treasury Constant Maturity Rate
2947 DGS2_mva365 2-Year Treasury Constant Maturity Rate 365 Day MA
2948 DGS2_mva200 2-Year Treasury Constant Maturity Rate 200 Day MA
2949 DGS2_mva050 2-Year Treasury Constant Maturity Rate 50 Day MA
2951 TB3MS_YoY4 3-Month Treasury Bill: Secondary Market Rate (Monthly) 4 Year over 4 Year
2953 TB3MS_Smooth Savitsky-Golay Smoothed (p=3, n=365) 3-Month Treasury Bill: Secondary Market Rate (Monthly)
2956 TB3MS_Log Log of 3-Month Treasury Bill: Secondary Market Rate (Monthly)
2957 TB3MS_mva365 3-Month Treasury Bill: Secondary Market Rate (Monthly) 365 Day MA
2958 TB3MS_mva200 3-Month Treasury Bill: Secondary Market Rate (Monthly) 200 Day MA
2959 TB3MS_mva050 3-Month Treasury Bill: Secondary Market Rate (Monthly) 50 Day MA
2963 DTB3_Smooth Savitsky-Golay Smoothed (p=3, n=365) 3-Month Treasury Bill: Secondary Market Rate (Daily)
2964 DTB3_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) 3-Month Treasury Bill: Secondary Market Rate (Daily)
2966 DTB3_Log Log of 3-Month Treasury Bill: Secondary Market Rate (Daily)
2967 DTB3_mva365 3-Month Treasury Bill: Secondary Market Rate (Daily) 365 Day MA
2968 DTB3_mva200 3-Month Treasury Bill: Secondary Market Rate (Daily) 200 Day MA
2969 DTB3_mva050 3-Month Treasury Bill: Secondary Market Rate (Daily) 50 Day MA
2973 IRX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2974 IRX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2976 IRX.Open_Log Log of
2977 IRX.Open_mva365 365 Day MA
2978 IRX.Open_mva200 200 Day MA
2979 IRX.Open_mva050 50 Day MA
2981 IRX.High_YoY4 4 Year over 4 Year
2983 IRX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2984 IRX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2986 IRX.High_Log Log of
2987 IRX.High_mva365 365 Day MA
2988 IRX.High_mva200 200 Day MA
2989 IRX.High_mva050 50 Day MA
2993 IRX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2994 IRX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2996 IRX.Low_Log Log of
2997 IRX.Low_mva365 365 Day MA
2998 IRX.Low_mva200 200 Day MA
2999 IRX.Low_mva050 50 Day MA
3003 IRX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3006 IRX.Close_Log Log of
3007 IRX.Close_mva365 365 Day MA
3008 IRX.Close_mva200 200 Day MA
3009 IRX.Close_mva050 50 Day MA
3010 IRX.Volume_YoY Year over Year
3011 IRX.Volume_YoY4 4 Year over 4 Year
3012 IRX.Volume_YoY5 5 Year over 5 Year
3013 IRX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3014 IRX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3015 IRX.Volume_SmoothDer Derivative of Smoothed
3016 IRX.Volume_Log Log of
3017 IRX.Volume_mva365 365 Day MA
3018 IRX.Volume_mva200 200 Day MA
3019 IRX.Volume_mva050 50 Day MA
3023 IRX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3026 IRX.Adjusted_Log Log of
3027 IRX.Adjusted_mva365 365 Day MA
3028 IRX.Adjusted_mva200 200 Day MA
3029 IRX.Adjusted_mva050 50 Day MA
3035 DCOILWTICO_SmoothDer Derivative of Smoothed Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma
3036 DCOILWTICO_Log Log of Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma
3045 DCOILBRENTEU_SmoothDer Derivative of Smoothed Crude Oil Prices: Brent - Europe
3053 NEWORDER_Smooth Savitsky-Golay Smoothed (p=3, n=365) Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft
3055 NEWORDER_SmoothDer Derivative of Smoothed Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft
3056 NEWORDER_Log Log of Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft
3057 NEWORDER_mva365 Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft 365 Day MA
3058 NEWORDER_mva200 Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft 200 Day MA
3059 NEWORDER_mva050 Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft 50 Day MA
3063 ALTSALES_Smooth Savitsky-Golay Smoothed (p=3, n=365) Light Weight Vehicle Sales: Autos and Light Trucks
3067 ALTSALES_mva365 Light Weight Vehicle Sales: Autos and Light Trucks 365 Day MA
3068 ALTSALES_mva200 Light Weight Vehicle Sales: Autos and Light Trucks 200 Day MA
3069 ALTSALES_mva050 Light Weight Vehicle Sales: Autos and Light Trucks 50 Day MA
3073 ICSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Initial Jobless Claims
3075 ICSA_SmoothDer Derivative of Smoothed Initial Jobless Claims
3077 ICSA_mva365 Initial Jobless Claims 365 Day MA
3078 ICSA_mva200 Initial Jobless Claims 200 Day MA
3079 ICSA_mva050 Initial Jobless Claims 50 Day MA
3083 GSPC.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3085 GSPC.Open_SmoothDer Derivative of Smoothed
3088 GSPC.Open_mva200 200 Day MA
3089 GSPC.Open_mva050 50 Day MA
3093 GSPC.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3095 GSPC.High_SmoothDer Derivative of Smoothed
3098 GSPC.High_mva200 200 Day MA
3099 GSPC.High_mva050 50 Day MA
3103 GSPC.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3105 GSPC.Low_SmoothDer Derivative of Smoothed
3108 GSPC.Low_mva200 200 Day MA
3109 GSPC.Low_mva050 50 Day MA
3113 GSPC.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3114 GSPC.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3115 GSPC.Close_SmoothDer Derivative of Smoothed
3118 GSPC.Close_mva200 200 Day MA
3119 GSPC.Close_mva050 50 Day MA
3133 GSPC.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3134 GSPC.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3135 GSPC.Adjusted_SmoothDer Derivative of Smoothed
3138 GSPC.Adjusted_mva200 200 Day MA
3139 GSPC.Adjusted_mva050 50 Day MA
3143 FXAIX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3145 FXAIX.Open_SmoothDer Derivative of Smoothed
3148 FXAIX.Open_mva200 200 Day MA
3149 FXAIX.Open_mva050 50 Day MA
3153 FXAIX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3155 FXAIX.High_SmoothDer Derivative of Smoothed
3158 FXAIX.High_mva200 200 Day MA
3159 FXAIX.High_mva050 50 Day MA
3163 FXAIX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3165 FXAIX.Low_SmoothDer Derivative of Smoothed
3168 FXAIX.Low_mva200 200 Day MA
3169 FXAIX.Low_mva050 50 Day MA
3173 FXAIX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3175 FXAIX.Close_SmoothDer Derivative of Smoothed
3178 FXAIX.Close_mva200 200 Day MA
3179 FXAIX.Close_mva050 50 Day MA
3180 FXAIX.Volume_YoY Year over Year
3181 FXAIX.Volume_YoY4 4 Year over 4 Year
3182 FXAIX.Volume_YoY5 5 Year over 5 Year
3183 FXAIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3184 FXAIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3185 FXAIX.Volume_SmoothDer Derivative of Smoothed
3186 FXAIX.Volume_Log Log of
3187 FXAIX.Volume_mva365 365 Day MA
3188 FXAIX.Volume_mva200 200 Day MA
3189 FXAIX.Volume_mva050 50 Day MA
3193 FXAIX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3195 FXAIX.Adjusted_SmoothDer Derivative of Smoothed
3198 FXAIX.Adjusted_mva200 200 Day MA
3199 FXAIX.Adjusted_mva050 50 Day MA
3208 FTIHX.Open_mva200 200 Day MA
3218 FTIHX.High_mva200 200 Day MA
3228 FTIHX.Low_mva200 200 Day MA
3238 FTIHX.Close_mva200 200 Day MA
3240 FTIHX.Volume_YoY Year over Year
3241 FTIHX.Volume_YoY4 4 Year over 4 Year
3242 FTIHX.Volume_YoY5 5 Year over 5 Year
3243 FTIHX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3244 FTIHX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3245 FTIHX.Volume_SmoothDer Derivative of Smoothed
3246 FTIHX.Volume_Log Log of
3247 FTIHX.Volume_mva365 365 Day MA
3248 FTIHX.Volume_mva200 200 Day MA
3249 FTIHX.Volume_mva050 50 Day MA
3258 FTIHX.Adjusted_mva200 200 Day MA
3268 MDIZX.Open_mva200 200 Day MA
3278 MDIZX.High_mva200 200 Day MA
3288 MDIZX.Low_mva200 200 Day MA
3298 MDIZX.Close_mva200 200 Day MA
3300 MDIZX.Volume_YoY Year over Year
3301 MDIZX.Volume_YoY4 4 Year over 4 Year
3302 MDIZX.Volume_YoY5 5 Year over 5 Year
3303 MDIZX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3304 MDIZX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3305 MDIZX.Volume_SmoothDer Derivative of Smoothed
3306 MDIZX.Volume_Log Log of
3307 MDIZX.Volume_mva365 365 Day MA
3308 MDIZX.Volume_mva200 200 Day MA
3309 MDIZX.Volume_mva050 50 Day MA
3317 MDIZX.Adjusted_mva365 365 Day MA
3318 MDIZX.Adjusted_mva200 200 Day MA
3360 DODIX.Volume_YoY Year over Year
3361 DODIX.Volume_YoY4 4 Year over 4 Year
3362 DODIX.Volume_YoY5 5 Year over 5 Year
3363 DODIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3364 DODIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3365 DODIX.Volume_SmoothDer Derivative of Smoothed
3366 DODIX.Volume_Log Log of
3367 DODIX.Volume_mva365 365 Day MA
3368 DODIX.Volume_mva200 200 Day MA
3369 DODIX.Volume_mva050 50 Day MA
3378 DODIX.Adjusted_mva200 200 Day MA
3383 RLG.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3385 RLG.Open_SmoothDer Derivative of Smoothed
3388 RLG.Open_mva200 200 Day MA
3389 RLG.Open_mva050 50 Day MA
3393 RLG.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3395 RLG.High_SmoothDer Derivative of Smoothed
3398 RLG.High_mva200 200 Day MA
3399 RLG.High_mva050 50 Day MA
3403 RLG.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3405 RLG.Low_SmoothDer Derivative of Smoothed
3408 RLG.Low_mva200 200 Day MA
3409 RLG.Low_mva050 50 Day MA
3413 RLG.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3415 RLG.Close_SmoothDer Derivative of Smoothed
3418 RLG.Close_mva200 200 Day MA
3419 RLG.Close_mva050 50 Day MA
3420 RLG.Volume_YoY Year over Year
3421 RLG.Volume_YoY4 4 Year over 4 Year
3422 RLG.Volume_YoY5 5 Year over 5 Year
3423 RLG.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3424 RLG.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3425 RLG.Volume_SmoothDer Derivative of Smoothed
3426 RLG.Volume_Log Log of
3427 RLG.Volume_mva365 365 Day MA
3428 RLG.Volume_mva200 200 Day MA
3429 RLG.Volume_mva050 50 Day MA
3433 RLG.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3435 RLG.Adjusted_SmoothDer Derivative of Smoothed
3438 RLG.Adjusted_mva200 200 Day MA
3439 RLG.Adjusted_mva050 50 Day MA
3447 DJI.Open_mva365 365 Day MA
3448 DJI.Open_mva200 200 Day MA
3449 DJI.Open_mva050 50 Day MA
3457 DJI.High_mva365 365 Day MA
3458 DJI.High_mva200 200 Day MA
3467 DJI.Low_mva365 365 Day MA
3468 DJI.Low_mva200 200 Day MA
3469 DJI.Low_mva050 50 Day MA
3474 DJI.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3477 DJI.Close_mva365 365 Day MA
3478 DJI.Close_mva200 200 Day MA
3479 DJI.Close_mva050 50 Day MA
3494 DJI.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3497 DJI.Adjusted_mva365 365 Day MA
3498 DJI.Adjusted_mva200 200 Day MA
3499 DJI.Adjusted_mva050 50 Day MA
3507 STOXX50E.Open_mva365 365 Day MA
3508 STOXX50E.Open_mva200 200 Day MA
3517 STOXX50E.High_mva365 365 Day MA
3518 STOXX50E.High_mva200 200 Day MA
3527 STOXX50E.Low_mva365 365 Day MA
3528 STOXX50E.Low_mva200 200 Day MA
3537 STOXX50E.Close_mva365 365 Day MA
3538 STOXX50E.Close_mva200 200 Day MA
3542 STOXX50E.Volume_YoY5 5 Year over 5 Year
3546 STOXX50E.Volume_Log Log of
3557 STOXX50E.Adjusted_mva365 365 Day MA
3558 STOXX50E.Adjusted_mva200 200 Day MA
3567 EFA.Open_mva365 365 Day MA
3568 EFA.Open_mva200 200 Day MA
3577 EFA.High_mva365 365 Day MA
3578 EFA.High_mva200 200 Day MA
3587 EFA.Low_mva365 365 Day MA
3588 EFA.Low_mva200 200 Day MA
3597 EFA.Close_mva365 365 Day MA
3598 EFA.Close_mva200 200 Day MA
3617 EFA.Adjusted_mva365 365 Day MA
3618 EFA.Adjusted_mva200 200 Day MA
3626 GDP_Log Log of Gross Domestic Product
3627 GDP_mva365 Gross Domestic Product 365 Day MA
3628 GDP_mva200 Gross Domestic Product 200 Day MA
3629 GDP_mva050 Gross Domestic Product 50 Day MA
3636 FNDEFX_Log Log of Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate)
3637 FNDEFX_mva365 Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate) 365 Day MA
3638 FNDEFX_mva200 Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate) 200 Day MA
3639 FNDEFX_mva050 Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate) 50 Day MA
3646 FDEFX_Log Log of Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate)
3647 FDEFX_mva365 Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate) 365 Day MA
3648 FDEFX_mva200 Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate) 200 Day MA
3649 FDEFX_mva050 Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate) 50 Day MA
3652 GDPNOW_YoY5 Fed Atlanta GDPNow 5 Year over 5 Year
3653 GDPNOW_Smooth Savitsky-Golay Smoothed (p=3, n=365) Fed Atlanta GDPNow
3655 GDPNOW_SmoothDer Derivative of Smoothed Fed Atlanta GDPNow
3656 GDPNOW_Log Log of Fed Atlanta GDPNow
3659 GDPNOW_mva050 Fed Atlanta GDPNow 50 Day MA
3666 GDPC1_Log Log of Real Gross Domestic Product
3667 GDPC1_mva365 Real Gross Domestic Product 365 Day MA
3668 GDPC1_mva200 Real Gross Domestic Product 200 Day MA
3669 GDPC1_mva050 Real Gross Domestic Product 50 Day MA
3676 GDPDEF_Log Log of Gross Domestic Product: Implicit Price Deflator
3677 GDPDEF_mva365 Gross Domestic Product: Implicit Price Deflator 365 Day MA
3678 GDPDEF_mva200 Gross Domestic Product: Implicit Price Deflator 200 Day MA
3679 GDPDEF_mva050 Gross Domestic Product: Implicit Price Deflator 50 Day MA
3683 VIG.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3687 VIG.Open_mva365 365 Day MA
3688 VIG.Open_mva200 200 Day MA
3689 VIG.Open_mva050 50 Day MA
3693 VIG.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3698 VIG.High_mva200 200 Day MA
3699 VIG.High_mva050 50 Day MA
3703 VIG.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3707 VIG.Low_mva365 365 Day MA
3708 VIG.Low_mva200 200 Day MA
3709 VIG.Low_mva050 50 Day MA
3713 VIG.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3717 VIG.Close_mva365 365 Day MA
3718 VIG.Close_mva200 200 Day MA
3719 VIG.Close_mva050 50 Day MA
3733 VIG.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3734 VIG.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3737 VIG.Adjusted_mva365 365 Day MA
3738 VIG.Adjusted_mva200 200 Day MA
3739 VIG.Adjusted_mva050 50 Day MA
3751 FEDFUNDS_YoY4 Effective Federal Funds Rate 4 Year over 4 Year
3756 FEDFUNDS_Log Log of Effective Federal Funds Rate
3757 FEDFUNDS_mva365 Effective Federal Funds Rate 365 Day MA
3758 FEDFUNDS_mva200 Effective Federal Funds Rate 200 Day MA
3759 FEDFUNDS_mva050 Effective Federal Funds Rate 50 Day MA
3763 GPDI_Smooth Savitsky-Golay Smoothed (p=3, n=365) Gross Private Domestic Investment
3765 GPDI_SmoothDer Derivative of Smoothed Gross Private Domestic Investment
3766 GPDI_Log Log of Gross Private Domestic Investment
3771 W790RC1Q027SBEA_YoY4 Net domestic investment: Private: Domestic busines 4 Year over 4 Year
3773 W790RC1Q027SBEA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Net domestic investment: Private: Domestic busines
3775 W790RC1Q027SBEA_SmoothDer Derivative of Smoothed Net domestic investment: Private: Domestic busines
3776 W790RC1Q027SBEA_Log Log of Net domestic investment: Private: Domestic busines
3780 MZMV_YoY Velocity of MZM Money Stock Year over Year
3781 MZMV_YoY4 Velocity of MZM Money Stock 4 Year over 4 Year
3786 MZMV_Log Log of Velocity of MZM Money Stock
3787 MZMV_mva365 Velocity of MZM Money Stock 365 Day MA
3788 MZMV_mva200 Velocity of MZM Money Stock 200 Day MA
3789 MZMV_mva050 Velocity of MZM Money Stock 50 Day MA
3790 M1_YoY M1 Money Stock Year over Year
3796 M1_Log Log of M1 Money Stock
3797 M1_mva365 M1 Money Stock 365 Day MA
3798 M1_mva200 M1 Money Stock 200 Day MA
3799 M1_mva050 M1 Money Stock 50 Day MA
3800 M2_YoY M2 Money Stock Year over Year
3806 M2_Log Log of M2 Money Stock
3807 M2_mva365 M2 Money Stock 365 Day MA
3808 M2_mva200 M2 Money Stock 200 Day MA
3809 M2_mva050 M2 Money Stock 50 Day MA
3813 OPHNFB_Smooth Savitsky-Golay Smoothed (p=3, n=365) Nonfarm Business Sector: Real Output Per Hour of All Persons, SA
3815 OPHNFB_SmoothDer Derivative of Smoothed Nonfarm Business Sector: Real Output Per Hour of All Persons, SA
3816 OPHNFB_Log Log of Nonfarm Business Sector: Real Output Per Hour of All Persons, SA
3823 IPMAN_Smooth Savitsky-Golay Smoothed (p=3, n=365) Industrial Production: Manufacturing (NAICS)
3825 IPMAN_SmoothDer Derivative of Smoothed Industrial Production: Manufacturing (NAICS)
3826 IPMAN_Log Log of Industrial Production: Manufacturing (NAICS)
3829 IPMAN_mva050 Industrial Production: Manufacturing (NAICS) 50 Day MA
3858 IWD.Low_mva200 200 Day MA
3868 IWD.Close_mva200 200 Day MA
3884 IWD.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3888 IWD.Adjusted_mva200 200 Day MA
3891 GS5_YoY4 5-Year Treasury Constant Maturity Rate 4 Year over 4 Year
3893 GS5_Smooth Savitsky-Golay Smoothed (p=3, n=365) 5-Year Treasury Constant Maturity Rate
3895 GS5_SmoothDer Derivative of Smoothed 5-Year Treasury Constant Maturity Rate
3896 GS5_Log Log of 5-Year Treasury Constant Maturity Rate
3897 GS5_mva365 5-Year Treasury Constant Maturity Rate 365 Day MA
3899 GS5_mva050 5-Year Treasury Constant Maturity Rate 50 Day MA
3906 PSAVERT_Log Log of Personal Saving Rate
3907 PSAVERT_mva365 Personal Saving Rate 365 Day MA
3908 PSAVERT_mva200 Personal Saving Rate 200 Day MA
3909 PSAVERT_mva050 Personal Saving Rate 50 Day MA
3925 VXX.Open_SmoothDer Derivative of Smoothed
3935 VXX.High_SmoothDer Derivative of Smoothed
3945 VXX.Low_SmoothDer Derivative of Smoothed
3955 VXX.Close_SmoothDer Derivative of Smoothed
3963 VXX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3966 VXX.Volume_Log Log of
3968 VXX.Volume_mva200 200 Day MA
3975 VXX.Adjusted_SmoothDer Derivative of Smoothed
3983 HOUST1F_Smooth Savitsky-Golay Smoothed (p=3, n=365) Privately Owned Housing Starts: 1-Unit Structures
3985 HOUST1F_SmoothDer Derivative of Smoothed Privately Owned Housing Starts: 1-Unit Structures
3986 HOUST1F_Log Log of Privately Owned Housing Starts: 1-Unit Structures
3988 HOUST1F_mva200 Privately Owned Housing Starts: 1-Unit Structures 200 Day MA
3989 HOUST1F_mva050 Privately Owned Housing Starts: 1-Unit Structures 50 Day MA
3993 GFDEBTN_Smooth Savitsky-Golay Smoothed (p=3, n=365) Federal Debt: Total Public Debt
3996 GFDEBTN_Log Log of Federal Debt: Total Public Debt
3997 GFDEBTN_mva365 Federal Debt: Total Public Debt 365 Day MA
3998 GFDEBTN_mva200 Federal Debt: Total Public Debt 200 Day MA
3999 GFDEBTN_mva050 Federal Debt: Total Public Debt 50 Day MA
4003 HOUST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Housing Starts: Total: New Privately Owned Housing Units Started, SA
4005 HOUST_SmoothDer Derivative of Smoothed Housing Starts: Total: New Privately Owned Housing Units Started, SA
4006 HOUST_Log Log of Housing Starts: Total: New Privately Owned Housing Units Started, SA
4008 HOUST_mva200 Housing Starts: Total: New Privately Owned Housing Units Started, SA 200 Day MA
4009 HOUST_mva050 Housing Starts: Total: New Privately Owned Housing Units Started, SA 50 Day MA
4013 HOUSTNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Housing Starts: Total: New Privately Owned Housing Units Started, NSA
4015 HOUSTNSA_SmoothDer Derivative of Smoothed Housing Starts: Total: New Privately Owned Housing Units Started, NSA
4016 HOUSTNSA_Log Log of Housing Starts: Total: New Privately Owned Housing Units Started, NSA
4018 HOUSTNSA_mva200 Housing Starts: Total: New Privately Owned Housing Units Started, NSA 200 Day MA
4019 HOUSTNSA_mva050 Housing Starts: Total: New Privately Owned Housing Units Started, NSA 50 Day MA
4020 EXHOSLUSM495S_YoY Existing Home Sales Year over Year
4025 EXHOSLUSM495S_SmoothDer Derivative of Smoothed Existing Home Sales
4033 MSPUS_Smooth Savitsky-Golay Smoothed (p=3, n=365) Median Sales Price of Houses Sold for the United States (NSA)
4035 MSPUS_SmoothDer Derivative of Smoothed Median Sales Price of Houses Sold for the United States (NSA)
4036 MSPUS_Log Log of Median Sales Price of Houses Sold for the United States (NSA)
4043 UMDMNO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Manufacturers’ New Orders: Durable Goods (NSA)
4045 UMDMNO_SmoothDer Derivative of Smoothed Manufacturers’ New Orders: Durable Goods (NSA)
4047 UMDMNO_mva365 Manufacturers’ New Orders: Durable Goods (NSA) 365 Day MA
4048 UMDMNO_mva200 Manufacturers’ New Orders: Durable Goods (NSA) 200 Day MA
4053 DGORDER_Smooth Savitsky-Golay Smoothed (p=3, n=365) Manufacturers’ New Orders: Durable Goods (SA)
4055 DGORDER_SmoothDer Derivative of Smoothed Manufacturers’ New Orders: Durable Goods (SA)
4056 DGORDER_Log Log of Manufacturers’ New Orders: Durable Goods (SA)
4057 DGORDER_mva365 Manufacturers’ New Orders: Durable Goods (SA) 365 Day MA
4058 DGORDER_mva200 Manufacturers’ New Orders: Durable Goods (SA) 200 Day MA
4059 DGORDER_mva050 Manufacturers’ New Orders: Durable Goods (SA) 50 Day MA
4063 CSUSHPINSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) S&P/Case-Shiller U.S. National Home Price Index (NSA)
4065 CSUSHPINSA_SmoothDer Derivative of Smoothed S&P/Case-Shiller U.S. National Home Price Index (NSA)
4066 CSUSHPINSA_Log Log of S&P/Case-Shiller U.S. National Home Price Index (NSA)
4069 CSUSHPINSA_mva050 S&P/Case-Shiller U.S. National Home Price Index (NSA) 50 Day MA
4070 GFDEGDQ188S_YoY Federal Debt: Total Public Debt as Percent of Gross Domestic Product Year over Year
4073 GFDEGDQ188S_Smooth Savitsky-Golay Smoothed (p=3, n=365) Federal Debt: Total Public Debt as Percent of Gross Domestic Product
4075 GFDEGDQ188S_SmoothDer Derivative of Smoothed Federal Debt: Total Public Debt as Percent of Gross Domestic Product
4076 GFDEGDQ188S_Log Log of Federal Debt: Total Public Debt as Percent of Gross Domestic Product
4080 FYFSD_YoY Federal Surplus or Deficit Year over Year
4083 FYFSD_Smooth Savitsky-Golay Smoothed (p=3, n=365) Federal Surplus or Deficit
4084 FYFSD_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Federal Surplus or Deficit
4086 FYFSD_Log Log of Federal Surplus or Deficit
4087 FYFSD_mva365 Federal Surplus or Deficit 365 Day MA
4088 FYFSD_mva200 Federal Surplus or Deficit 200 Day MA
4089 FYFSD_mva050 Federal Surplus or Deficit 50 Day MA
4090 FYFSGDA188S_YoY Federal Surplus or Deficit [-] as Percent of Gross Domestic Product Year over Year
4094 FYFSGDA188S_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Federal Surplus or Deficit [-] as Percent of Gross Domestic Product
4096 FYFSGDA188S_Log Log of Federal Surplus or Deficit [-] as Percent of Gross Domestic Product
4097 FYFSGDA188S_mva365 Federal Surplus or Deficit [-] as Percent of Gross Domestic Product 365 Day MA
4098 FYFSGDA188S_mva200 Federal Surplus or Deficit [-] as Percent of Gross Domestic Product 200 Day MA
4099 FYFSGDA188S_mva050 Federal Surplus or Deficit [-] as Percent of Gross Domestic Product 50 Day MA
4100 GDX.Open_YoY Year over Year
4108 GDX.Open_mva200 200 Day MA
4110 GDX.High_YoY Year over Year
4118 GDX.High_mva200 200 Day MA
4120 GDX.Low_YoY Year over Year
4128 GDX.Low_mva200 200 Day MA
4130 GDX.Close_YoY Year over Year
4138 GDX.Close_mva200 200 Day MA
4150 GDX.Adjusted_YoY Year over Year
4158 GDX.Adjusted_mva200 200 Day MA
4187 XLE.Low_mva365 365 Day MA
4217 XLE.Adjusted_mva365 365 Day MA
4225 GSG.Open_SmoothDer Derivative of Smoothed
4235 GSG.High_SmoothDer Derivative of Smoothed
4245 GSG.Low_SmoothDer Derivative of Smoothed
4255 GSG.Close_SmoothDer Derivative of Smoothed
4275 GSG.Adjusted_SmoothDer Derivative of Smoothed
4285 WALCL_SmoothDer Derivative of Smoothed All Federal Reserve Banks: Total Assets
4291 OUTMS_YoY4 Manufacturing Sector: Real Output 4 Year over 4 Year
4295 OUTMS_SmoothDer Derivative of Smoothed Manufacturing Sector: Real Output
4296 OUTMS_Log Log of Manufacturing Sector: Real Output
4303 MANEMP_Smooth Savitsky-Golay Smoothed (p=3, n=365) All Employees: Manufacturing
4306 MANEMP_Log Log of All Employees: Manufacturing
4307 MANEMP_mva365 All Employees: Manufacturing 365 Day MA
4308 MANEMP_mva200 All Employees: Manufacturing 200 Day MA
4309 MANEMP_mva050 All Employees: Manufacturing 50 Day MA
4310 PRS30006163_YoY Manufacturing Sector: Real Output Per Person Year over Year
4311 PRS30006163_YoY4 Manufacturing Sector: Real Output Per Person 4 Year over 4 Year
4315 PRS30006163_SmoothDer Derivative of Smoothed Manufacturing Sector: Real Output Per Person
4316 PRS30006163_Log Log of Manufacturing Sector: Real Output Per Person
4323 BAMLC0A3CA_Smooth Savitsky-Golay Smoothed (p=3, n=365) ICE BofAML US Corporate A Option-Adjusted Spread
4325 BAMLC0A3CA_SmoothDer Derivative of Smoothed ICE BofAML US Corporate A Option-Adjusted Spread
4331 AAA_YoY4 Moody’s Seasoned Aaa Corporate Bond Yield 4 Year over 4 Year
4333 AAA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Moody’s Seasoned Aaa Corporate Bond Yield
4335 AAA_SmoothDer Derivative of Smoothed Moody’s Seasoned Aaa Corporate Bond Yield
4337 AAA_mva365 Moody’s Seasoned Aaa Corporate Bond Yield 365 Day MA
4347 SOFR_mva365 Secured Overnight Financing Rate 365 Day MA
4348 SOFR_mva200 Secured Overnight Financing Rate 200 Day MA
4349 SOFR_mva050 Secured Overnight Financing Rate 50 Day MA
4353 SOFRVOL_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Volume
4355 SOFRVOL_SmoothDer Derivative of Smoothed Secured Overnight Financing Volume
4357 SOFRVOL_mva365 Secured Overnight Financing Volume 365 Day MA
4358 SOFRVOL_mva200 Secured Overnight Financing Volume 200 Day MA
4359 SOFRVOL_mva050 Secured Overnight Financing Volume 50 Day MA
4363 SOFR99_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 99th Percentile
4367 SOFR99_mva365 Secured Overnight Financing Rate: 99th Percentile 365 Day MA
4368 SOFR99_mva200 Secured Overnight Financing Rate: 99th Percentile 200 Day MA
4369 SOFR99_mva050 Secured Overnight Financing Rate: 99th Percentile 50 Day MA
4377 SOFR75_mva365 Secured Overnight Financing Rate: 75th Percentile 365 Day MA
4378 SOFR75_mva200 Secured Overnight Financing Rate: 75th Percentile 200 Day MA
4379 SOFR75_mva050 Secured Overnight Financing Rate: 75th Percentile 50 Day MA
4386 SOFR25_Log Log of Secured Overnight Financing Rate: 25th Percentile
4387 SOFR25_mva365 Secured Overnight Financing Rate: 25th Percentile 365 Day MA
4388 SOFR25_mva200 Secured Overnight Financing Rate: 25th Percentile 200 Day MA
4389 SOFR25_mva050 Secured Overnight Financing Rate: 25th Percentile 50 Day MA
4396 SOFR1_Log Log of Secured Overnight Financing Rate: 1st Percentile
4397 SOFR1_mva365 Secured Overnight Financing Rate: 1st Percentile 365 Day MA
4398 SOFR1_mva200 Secured Overnight Financing Rate: 1st Percentile 200 Day MA
4399 SOFR1_mva050 Secured Overnight Financing Rate: 1st Percentile 50 Day MA
4407 OBFR_mva365 Overnight Bank Funding Rate 365 Day MA
4408 OBFR_mva200 Overnight Bank Funding Rate 200 Day MA
4414 OBFR99_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Overnight Bank Funding Rate: 99th Percentile
4417 OBFR99_mva365 Overnight Bank Funding Rate: 99th Percentile 365 Day MA
4418 OBFR99_mva200 Overnight Bank Funding Rate: 99th Percentile 200 Day MA
4419 OBFR99_mva050 Overnight Bank Funding Rate: 99th Percentile 50 Day MA
4426 OBFR75_Log Log of Overnight Bank Funding Rate: 75th Percentile
4427 OBFR75_mva365 Overnight Bank Funding Rate: 75th Percentile 365 Day MA
4428 OBFR75_mva200 Overnight Bank Funding Rate: 75th Percentile 200 Day MA
4429 OBFR75_mva050 Overnight Bank Funding Rate: 75th Percentile 50 Day MA
4436 OBFR25_Log Log of Overnight Bank Funding Rate: 25th Percentile
4437 OBFR25_mva365 Overnight Bank Funding Rate: 25th Percentile 365 Day MA
4438 OBFR25_mva200 Overnight Bank Funding Rate: 25th Percentile 200 Day MA
4441 OBFR1_YoY4 Overnight Bank Funding Rate: 1st Percentile 4 Year over 4 Year
4446 OBFR1_Log Log of Overnight Bank Funding Rate: 1st Percentile
4447 OBFR1_mva365 Overnight Bank Funding Rate: 1st Percentile 365 Day MA
4448 OBFR1_mva200 Overnight Bank Funding Rate: 1st Percentile 200 Day MA
4456 RPONTSYD_Log Log of Overnight Repurchase Agreements: Treasury Securities Purchased by the Federal Reserve in the Temporary Open Market Operations
4460 IOER_YoY Interest Rate on Excess Reserves Year over Year
4461 IOER_YoY4 Interest Rate on Excess Reserves 4 Year over 4 Year
4466 IOER_Log Log of Interest Rate on Excess Reserves
4467 IOER_mva365 Interest Rate on Excess Reserves 365 Day MA
4468 IOER_mva200 Interest Rate on Excess Reserves 200 Day MA
4469 IOER_mva050 Interest Rate on Excess Reserves 50 Day MA
4480 EXCSRESNW_YoY Excess Reserves of Depository Institutions Year over Year
4486 EXCSRESNW_Log Log of Excess Reserves of Depository Institutions
4487 EXCSRESNW_mva365 Excess Reserves of Depository Institutions 365 Day MA
4488 EXCSRESNW_mva200 Excess Reserves of Depository Institutions 200 Day MA
4489 EXCSRESNW_mva050 Excess Reserves of Depository Institutions 50 Day MA
4490 ECBASSETS_YoY Central Bank Assets for Euro Area (11-19 Countries) Year over Year
4496 ECBASSETS_Log Log of Central Bank Assets for Euro Area (11-19 Countries)
4497 ECBASSETS_mva365 Central Bank Assets for Euro Area (11-19 Countries) 365 Day MA
4498 ECBASSETS_mva200 Central Bank Assets for Euro Area (11-19 Countries) 200 Day MA
4499 ECBASSETS_mva050 Central Bank Assets for Euro Area (11-19 Countries) 50 Day MA
4506 EUNNGDP_Log Log of Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries)
4507 EUNNGDP_mva365 Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries) 365 Day MA
4508 EUNNGDP_mva200 Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries) 200 Day MA
4509 EUNNGDP_mva050 Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries) 50 Day MA
4513 CEU0600000007_Smooth Savitsky-Golay Smoothed (p=3, n=365) Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing
4515 CEU0600000007_SmoothDer Derivative of Smoothed Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing
4516 CEU0600000007_Log Log of Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing
4519 CEU0600000007_mva050 Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing 50 Day MA
4520 CURRENCY_YoY Currency Component of M1 (Seasonally Adjusted) Year over Year
4526 CURRENCY_Log Log of Currency Component of M1 (Seasonally Adjusted)
4527 CURRENCY_mva365 Currency Component of M1 (Seasonally Adjusted) 365 Day MA
4528 CURRENCY_mva200 Currency Component of M1 (Seasonally Adjusted) 200 Day MA
4529 CURRENCY_mva050 Currency Component of M1 (Seasonally Adjusted) 50 Day MA
4533 WCURRNS_Smooth Savitsky-Golay Smoothed (p=3, n=365) Currency Component of M1
4535 WCURRNS_SmoothDer Derivative of Smoothed Currency Component of M1
4536 WCURRNS_Log Log of Currency Component of M1
4537 WCURRNS_mva365 Currency Component of M1 365 Day MA
4538 WCURRNS_mva200 Currency Component of M1 200 Day MA
4539 WCURRNS_mva050 Currency Component of M1 50 Day MA
4542 BOGMBASE_YoY5 Monetary Base; Total 5 Year over 5 Year
4548 BOGMBASE_mva200 Monetary Base; Total 200 Day MA
4553 PRS88003193_Smooth Savitsky-Golay Smoothed (p=3, n=365) Nonfinancial Corporations Sector: Unit Profits
4555 PRS88003193_SmoothDer Derivative of Smoothed Nonfinancial Corporations Sector: Unit Profits
4556 PRS88003193_Log Log of Nonfinancial Corporations Sector: Unit Profits
4565 PPIACO_SmoothDer Derivative of Smoothed Producer Price Index for All Commodities
4575 PCUOMFGOMFG_SmoothDer Derivative of Smoothed Producer Price Index by Industry: Total Manufacturing Industries
4586 POPTHM_Smooth Savitsky-Golay Smoothed (p=3, n=365) Population (U.S.)
4587 POPTHM_Smooth Savitsky-Golay Smoothed (p=3, n=365) Population (U.S.)
4592 POPTHM_Log Log of Population (U.S.)
4593 POPTHM_Log Log of Population (U.S.)
4594 POPTHM_mva365 Population (U.S.) 365 Day MA
4595 POPTHM_mva365 Population (U.S.) 365 Day MA
4596 POPTHM_mva200 Population (U.S.) 200 Day MA
4597 POPTHM_mva200 Population (U.S.) 200 Day MA
4598 POPTHM_mva050 Population (U.S.) 50 Day MA
4599 POPTHM_mva050 Population (U.S.) 50 Day MA
4606 POPTHM.1_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4607 POPTHM.1_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4612 POPTHM.1_Log Log of
4613 POPTHM.1_Log Log of
4614 POPTHM.1_mva365 365 Day MA
4615 POPTHM.1_mva365 365 Day MA
4616 POPTHM.1_mva200 200 Day MA
4617 POPTHM.1_mva200 200 Day MA
4618 POPTHM.1_mva050 50 Day MA
4619 POPTHM.1_mva050 50 Day MA
4626 CLF16OV_Log Log of Civilian Labor Force Level, SA
4627 CLF16OV_mva365 Civilian Labor Force Level, SA 365 Day MA
4628 CLF16OV_mva200 Civilian Labor Force Level, SA 200 Day MA
4629 CLF16OV_mva050 Civilian Labor Force Level, SA 50 Day MA
4633 LNU01000000_Smooth Savitsky-Golay Smoothed (p=3, n=365) Civilian Labor Force Level, NSA
4635 LNU01000000_SmoothDer Derivative of Smoothed Civilian Labor Force Level, NSA
4636 LNU01000000_Log Log of Civilian Labor Force Level, NSA
4637 LNU01000000_mva365 Civilian Labor Force Level, NSA 365 Day MA
4638 LNU01000000_mva200 Civilian Labor Force Level, NSA 200 Day MA
4639 LNU01000000_mva050 Civilian Labor Force Level, NSA 50 Day MA
4643 LNU03000000_Smooth Savitsky-Golay Smoothed (p=3, n=365) Unemployment Level (NSA)
4645 LNU03000000_SmoothDer Derivative of Smoothed Unemployment Level (NSA)
4648 LNU03000000_mva200 Unemployment Level (NSA) 200 Day MA
4653 UNEMPLOY_Smooth Savitsky-Golay Smoothed (p=3, n=365) Unemployment Level, seasonally adjusted
4655 UNEMPLOY_SmoothDer Derivative of Smoothed Unemployment Level, seasonally adjusted
4658 UNEMPLOY_mva200 Unemployment Level, seasonally adjusted 200 Day MA
4663 RSAFS_Smooth Savitsky-Golay Smoothed (p=3, n=365) Advance Retail Sales: Retail and Food Services
4665 RSAFS_SmoothDer Derivative of Smoothed Advance Retail Sales: Retail and Food Services
4667 RSAFS_mva365 Advance Retail Sales: Retail and Food Services 365 Day MA
4675 FRGSHPUSM649NCIS_SmoothDer Derivative of Smoothed Cass Freight Index: Shipments
4680 BOPGTB_YoY Trade Balance: Goods, Balance of Payments Basis (SA) Year over Year
4685 BOPGTB_SmoothDer Derivative of Smoothed Trade Balance: Goods, Balance of Payments Basis (SA)
4686 BOPGTB_Log Log of Trade Balance: Goods, Balance of Payments Basis (SA)
4691 TERMCBPER24NS_YoY4 Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan 4 Year over 4 Year
4692 TERMCBPER24NS_YoY5 Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan 5 Year over 5 Year
4696 TERMCBPER24NS_Log Log of Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan
4697 TERMCBPER24NS_mva365 Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan 365 Day MA
4698 TERMCBPER24NS_mva200 Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan 200 Day MA
4699 TERMCBPER24NS_mva050 Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan 50 Day MA
4700 A065RC1A027NBEA_YoY Personal income (NSA) Year over Year
4706 A065RC1A027NBEA_Log Log of Personal income (NSA)
4707 A065RC1A027NBEA_mva365 Personal income (NSA) 365 Day MA
4708 A065RC1A027NBEA_mva200 Personal income (NSA) 200 Day MA
4709 A065RC1A027NBEA_mva050 Personal income (NSA) 50 Day MA
4716 PI_Log Log of Personal income (SA)
4717 PI_mva365 Personal income (SA) 365 Day MA
4718 PI_mva200 Personal income (SA) 200 Day MA
4719 PI_mva050 Personal income (SA) 50 Day MA
4726 PCE_Log Log of Personal Consumption Expenditures (SA)
4727 PCE_mva365 Personal Consumption Expenditures (SA) 365 Day MA
4728 PCE_mva200 Personal Consumption Expenditures (SA) 200 Day MA
4729 PCE_mva050 Personal Consumption Expenditures (SA) 50 Day MA
4730 A053RC1Q027SBEA_YoY National income: Corporate profits before tax (without IVA and CCAdj) Year over Year
4735 A053RC1Q027SBEA_SmoothDer Derivative of Smoothed National income: Corporate profits before tax (without IVA and CCAdj)
4736 A053RC1Q027SBEA_Log Log of National income: Corporate profits before tax (without IVA and CCAdj)
4745 CPROFIT_SmoothDer Derivative of Smoothed Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj)
4746 CPROFIT_Log Log of Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj)
4753 SPY.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4755 SPY.Open_SmoothDer Derivative of Smoothed
4758 SPY.Open_mva200 200 Day MA
4759 SPY.Open_mva050 50 Day MA
4763 SPY.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4765 SPY.High_SmoothDer Derivative of Smoothed
4768 SPY.High_mva200 200 Day MA
4769 SPY.High_mva050 50 Day MA
4773 SPY.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4775 SPY.Low_SmoothDer Derivative of Smoothed
4778 SPY.Low_mva200 200 Day MA
4779 SPY.Low_mva050 50 Day MA
4783 SPY.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4784 SPY.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4785 SPY.Close_SmoothDer Derivative of Smoothed
4788 SPY.Close_mva200 200 Day MA
4789 SPY.Close_mva050 50 Day MA
4803 SPY.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4804 SPY.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4805 SPY.Adjusted_SmoothDer Derivative of Smoothed
4808 SPY.Adjusted_mva200 200 Day MA
4809 SPY.Adjusted_mva050 50 Day MA
4818 MDY.Open_mva200 200 Day MA
4828 MDY.High_mva200 200 Day MA
4837 MDY.Low_mva365 365 Day MA
4838 MDY.Low_mva200 200 Day MA
4848 MDY.Close_mva200 200 Day MA
4853 MDY.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4864 MDY.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4867 MDY.Adjusted_mva365 365 Day MA
4868 MDY.Adjusted_mva200 200 Day MA
4916 EES.Volume_Log Log of
4993 VGSTX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4995 VGSTX.Open_SmoothDer Derivative of Smoothed
4999 VGSTX.Open_mva050 50 Day MA
5003 VGSTX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5005 VGSTX.High_SmoothDer Derivative of Smoothed
5009 VGSTX.High_mva050 50 Day MA
5013 VGSTX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5015 VGSTX.Low_SmoothDer Derivative of Smoothed
5019 VGSTX.Low_mva050 50 Day MA
5023 VGSTX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5025 VGSTX.Close_SmoothDer Derivative of Smoothed
5029 VGSTX.Close_mva050 50 Day MA
5030 VGSTX.Volume_YoY Year over Year
5031 VGSTX.Volume_YoY4 4 Year over 4 Year
5032 VGSTX.Volume_YoY5 5 Year over 5 Year
5033 VGSTX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5034 VGSTX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5035 VGSTX.Volume_SmoothDer Derivative of Smoothed
5036 VGSTX.Volume_Log Log of
5037 VGSTX.Volume_mva365 365 Day MA
5038 VGSTX.Volume_mva200 200 Day MA
5039 VGSTX.Volume_mva050 50 Day MA
5048 VGSTX.Adjusted_mva200 200 Day MA
5049 VGSTX.Adjusted_mva050 50 Day MA
5053 VFINX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5054 VFINX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5055 VFINX.Open_SmoothDer Derivative of Smoothed
5058 VFINX.Open_mva200 200 Day MA
5059 VFINX.Open_mva050 50 Day MA
5063 VFINX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5064 VFINX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5065 VFINX.High_SmoothDer Derivative of Smoothed
5068 VFINX.High_mva200 200 Day MA
5069 VFINX.High_mva050 50 Day MA
5073 VFINX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5074 VFINX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5075 VFINX.Low_SmoothDer Derivative of Smoothed
5078 VFINX.Low_mva200 200 Day MA
5079 VFINX.Low_mva050 50 Day MA
5083 VFINX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5084 VFINX.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5085 VFINX.Close_SmoothDer Derivative of Smoothed
5088 VFINX.Close_mva200 200 Day MA
5089 VFINX.Close_mva050 50 Day MA
5090 VFINX.Volume_YoY Year over Year
5091 VFINX.Volume_YoY4 4 Year over 4 Year
5092 VFINX.Volume_YoY5 5 Year over 5 Year
5093 VFINX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5094 VFINX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5095 VFINX.Volume_SmoothDer Derivative of Smoothed
5096 VFINX.Volume_Log Log of
5097 VFINX.Volume_mva365 365 Day MA
5098 VFINX.Volume_mva200 200 Day MA
5099 VFINX.Volume_mva050 50 Day MA
5103 VFINX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5104 VFINX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5105 VFINX.Adjusted_SmoothDer Derivative of Smoothed
5108 VFINX.Adjusted_mva200 200 Day MA
5109 VFINX.Adjusted_mva050 50 Day MA
5155 VOE.Volume_SmoothDer Derivative of Smoothed
5173 VOT.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5174 VOT.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5176 VOT.Open_Log Log of
5178 VOT.Open_mva200 200 Day MA
5179 VOT.Open_mva050 50 Day MA
5183 VOT.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5184 VOT.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5186 VOT.High_Log Log of
5188 VOT.High_mva200 200 Day MA
5189 VOT.High_mva050 50 Day MA
5193 VOT.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5194 VOT.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5196 VOT.Low_Log Log of
5198 VOT.Low_mva200 200 Day MA
5199 VOT.Low_mva050 50 Day MA
5203 VOT.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5204 VOT.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5206 VOT.Close_Log Log of
5208 VOT.Close_mva200 200 Day MA
5209 VOT.Close_mva050 50 Day MA
5215 VOT.Volume_SmoothDer Derivative of Smoothed
5223 VOT.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5224 VOT.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5226 VOT.Adjusted_Log Log of
5228 VOT.Adjusted_mva200 200 Day MA
5229 VOT.Adjusted_mva050 50 Day MA
5230 TMFGX.Open_YoY Year over Year
5232 TMFGX.Open_YoY5 5 Year over 5 Year
5236 TMFGX.Open_Log Log of
5237 TMFGX.Open_mva365 365 Day MA
5238 TMFGX.Open_mva200 200 Day MA
5239 TMFGX.Open_mva050 50 Day MA
5240 TMFGX.High_YoY Year over Year
5242 TMFGX.High_YoY5 5 Year over 5 Year
5246 TMFGX.High_Log Log of
5247 TMFGX.High_mva365 365 Day MA
5248 TMFGX.High_mva200 200 Day MA
5249 TMFGX.High_mva050 50 Day MA
5250 TMFGX.Low_YoY Year over Year
5252 TMFGX.Low_YoY5 5 Year over 5 Year
5256 TMFGX.Low_Log Log of
5257 TMFGX.Low_mva365 365 Day MA
5258 TMFGX.Low_mva200 200 Day MA
5259 TMFGX.Low_mva050 50 Day MA
5260 TMFGX.Close_YoY Year over Year
5262 TMFGX.Close_YoY5 5 Year over 5 Year
5266 TMFGX.Close_Log Log of
5267 TMFGX.Close_mva365 365 Day MA
5268 TMFGX.Close_mva200 200 Day MA
5269 TMFGX.Close_mva050 50 Day MA
5270 TMFGX.Volume_YoY Year over Year
5271 TMFGX.Volume_YoY4 4 Year over 4 Year
5272 TMFGX.Volume_YoY5 5 Year over 5 Year
5273 TMFGX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5274 TMFGX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5275 TMFGX.Volume_SmoothDer Derivative of Smoothed
5276 TMFGX.Volume_Log Log of
5277 TMFGX.Volume_mva365 365 Day MA
5278 TMFGX.Volume_mva200 200 Day MA
5279 TMFGX.Volume_mva050 50 Day MA
5280 TMFGX.Adjusted_YoY Year over Year
5282 TMFGX.Adjusted_YoY5 5 Year over 5 Year
5286 TMFGX.Adjusted_Log Log of
5287 TMFGX.Adjusted_mva365 365 Day MA
5288 TMFGX.Adjusted_mva200 200 Day MA
5289 TMFGX.Adjusted_mva050 50 Day MA
5293 IWM.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5303 IWM.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5313 IWM.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5323 IWM.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5333 IWM.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5335 IWM.Volume_SmoothDer Derivative of Smoothed
5343 IWM.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5348 IWM.Adjusted_mva200 200 Day MA
5353 ONEQ.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5355 ONEQ.Open_SmoothDer Derivative of Smoothed
5358 ONEQ.Open_mva200 200 Day MA
5359 ONEQ.Open_mva050 50 Day MA
5363 ONEQ.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5365 ONEQ.High_SmoothDer Derivative of Smoothed
5368 ONEQ.High_mva200 200 Day MA
5369 ONEQ.High_mva050 50 Day MA
5373 ONEQ.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5375 ONEQ.Low_SmoothDer Derivative of Smoothed
5378 ONEQ.Low_mva200 200 Day MA
5379 ONEQ.Low_mva050 50 Day MA
5383 ONEQ.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5385 ONEQ.Close_SmoothDer Derivative of Smoothed
5388 ONEQ.Close_mva200 200 Day MA
5389 ONEQ.Close_mva050 50 Day MA
5403 ONEQ.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5405 ONEQ.Adjusted_SmoothDer Derivative of Smoothed
5408 ONEQ.Adjusted_mva200 200 Day MA
5409 ONEQ.Adjusted_mva050 50 Day MA
5413 FSMAX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5414 FSMAX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5418 FSMAX.Open_mva200 200 Day MA
5423 FSMAX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5424 FSMAX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5428 FSMAX.High_mva200 200 Day MA
5433 FSMAX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5434 FSMAX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5438 FSMAX.Low_mva200 200 Day MA
5443 FSMAX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5444 FSMAX.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5448 FSMAX.Close_mva200 200 Day MA
5450 FSMAX.Volume_YoY Year over Year
5451 FSMAX.Volume_YoY4 4 Year over 4 Year
5452 FSMAX.Volume_YoY5 5 Year over 5 Year
5453 FSMAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5454 FSMAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5455 FSMAX.Volume_SmoothDer Derivative of Smoothed
5456 FSMAX.Volume_Log Log of
5457 FSMAX.Volume_mva365 365 Day MA
5458 FSMAX.Volume_mva200 200 Day MA
5459 FSMAX.Volume_mva050 50 Day MA
5463 FSMAX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5464 FSMAX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5468 FSMAX.Adjusted_mva200 200 Day MA
5510 FXNAX.Volume_YoY Year over Year
5511 FXNAX.Volume_YoY4 4 Year over 4 Year
5512 FXNAX.Volume_YoY5 5 Year over 5 Year
5513 FXNAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5514 FXNAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5515 FXNAX.Volume_SmoothDer Derivative of Smoothed
5516 FXNAX.Volume_Log Log of
5517 FXNAX.Volume_mva365 365 Day MA
5518 FXNAX.Volume_mva200 200 Day MA
5519 FXNAX.Volume_mva050 50 Day MA
5530 HAINX.Open_YoY Year over Year
5537 HAINX.Open_mva365 365 Day MA
5538 HAINX.Open_mva200 200 Day MA
5540 HAINX.High_YoY Year over Year
5547 HAINX.High_mva365 365 Day MA
5548 HAINX.High_mva200 200 Day MA
5550 HAINX.Low_YoY Year over Year
5557 HAINX.Low_mva365 365 Day MA
5558 HAINX.Low_mva200 200 Day MA
5560 HAINX.Close_YoY Year over Year
5567 HAINX.Close_mva365 365 Day MA
5568 HAINX.Close_mva200 200 Day MA
5570 HAINX.Volume_YoY Year over Year
5571 HAINX.Volume_YoY4 4 Year over 4 Year
5572 HAINX.Volume_YoY5 5 Year over 5 Year
5573 HAINX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5574 HAINX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5575 HAINX.Volume_SmoothDer Derivative of Smoothed
5576 HAINX.Volume_Log Log of
5577 HAINX.Volume_mva365 365 Day MA
5578 HAINX.Volume_mva200 200 Day MA
5579 HAINX.Volume_mva050 50 Day MA
5580 HAINX.Adjusted_YoY Year over Year
5587 HAINX.Adjusted_mva365 365 Day MA
5588 HAINX.Adjusted_mva200 200 Day MA
5593 HNACX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5595 HNACX.Open_SmoothDer Derivative of Smoothed
5598 HNACX.Open_mva200 200 Day MA
5599 HNACX.Open_mva050 50 Day MA
5603 HNACX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5605 HNACX.High_SmoothDer Derivative of Smoothed
5608 HNACX.High_mva200 200 Day MA
5609 HNACX.High_mva050 50 Day MA
5613 HNACX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5615 HNACX.Low_SmoothDer Derivative of Smoothed
5618 HNACX.Low_mva200 200 Day MA
5619 HNACX.Low_mva050 50 Day MA
5623 HNACX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5625 HNACX.Close_SmoothDer Derivative of Smoothed
5628 HNACX.Close_mva200 200 Day MA
5629 HNACX.Close_mva050 50 Day MA
5630 HNACX.Volume_YoY Year over Year
5631 HNACX.Volume_YoY4 4 Year over 4 Year
5632 HNACX.Volume_YoY5 5 Year over 5 Year
5633 HNACX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5634 HNACX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5635 HNACX.Volume_SmoothDer Derivative of Smoothed
5636 HNACX.Volume_Log Log of
5637 HNACX.Volume_mva365 365 Day MA
5638 HNACX.Volume_mva200 200 Day MA
5639 HNACX.Volume_mva050 50 Day MA
5643 HNACX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5645 HNACX.Adjusted_SmoothDer Derivative of Smoothed
5648 HNACX.Adjusted_mva200 200 Day MA
5649 HNACX.Adjusted_mva050 50 Day MA
5658 VEU.Open_mva200 200 Day MA
5668 VEU.High_mva200 200 Day MA
5678 VEU.Low_mva200 200 Day MA
5688 VEU.Close_mva200 200 Day MA
5707 VEU.Adjusted_mva365 365 Day MA
5708 VEU.Adjusted_mva200 200 Day MA
5750 VEIRX.Volume_YoY Year over Year
5751 VEIRX.Volume_YoY4 4 Year over 4 Year
5752 VEIRX.Volume_YoY5 5 Year over 5 Year
5753 VEIRX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5754 VEIRX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5755 VEIRX.Volume_SmoothDer Derivative of Smoothed
5756 VEIRX.Volume_Log Log of
5757 VEIRX.Volume_mva365 365 Day MA
5758 VEIRX.Volume_mva200 200 Day MA
5759 VEIRX.Volume_mva050 50 Day MA
5767 VEIRX.Adjusted_mva365 365 Day MA
5777 BIL.Open_mva365 365 Day MA
5778 BIL.Open_mva200 200 Day MA
5787 BIL.High_mva365 365 Day MA
5788 BIL.High_mva200 200 Day MA
5797 BIL.Low_mva365 365 Day MA
5798 BIL.Low_mva200 200 Day MA
5807 BIL.Close_mva365 365 Day MA
5808 BIL.Close_mva200 200 Day MA
5820 BIL.Adjusted_YoY Year over Year
5823 BIL.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5824 BIL.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5825 BIL.Adjusted_SmoothDer Derivative of Smoothed
5826 BIL.Adjusted_Log Log of
5827 BIL.Adjusted_mva365 365 Day MA
5828 BIL.Adjusted_mva200 200 Day MA
5829 BIL.Adjusted_mva050 50 Day MA
5838 IVOO.Open_mva200 200 Day MA
5848 IVOO.High_mva200 200 Day MA
5857 IVOO.Low_mva365 365 Day MA
5858 IVOO.Low_mva200 200 Day MA
5868 IVOO.Close_mva200 200 Day MA
5876 IVOO.Volume_Log Log of
5884 IVOO.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5887 IVOO.Adjusted_mva365 365 Day MA
5888 IVOO.Adjusted_mva200 200 Day MA
5894 VO.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5898 VO.Open_mva200 200 Day MA
5904 VO.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5908 VO.High_mva200 200 Day MA
5914 VO.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5918 VO.Low_mva200 200 Day MA
5924 VO.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5928 VO.Close_mva200 200 Day MA
5936 VO.Volume_Log Log of
5944 VO.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5948 VO.Adjusted_mva200 200 Day MA
5996 CZA.Volume_Log Log of
6055 VYM.Volume_SmoothDer Derivative of Smoothed
6073 ACWI.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6078 ACWI.Open_mva200 200 Day MA
6079 ACWI.Open_mva050 50 Day MA
6088 ACWI.High_mva200 200 Day MA
6089 ACWI.High_mva050 50 Day MA
6093 ACWI.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6098 ACWI.Low_mva200 200 Day MA
6099 ACWI.Low_mva050 50 Day MA
6104 ACWI.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
6108 ACWI.Close_mva200 200 Day MA
6109 ACWI.Close_mva050 50 Day MA
6123 ACWI.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6124 ACWI.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
6128 ACWI.Adjusted_mva200 200 Day MA
6129 ACWI.Adjusted_mva050 50 Day MA
6176 SLY.Volume_Log Log of
6193 QQQ.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6195 QQQ.Open_SmoothDer Derivative of Smoothed
6198 QQQ.Open_mva200 200 Day MA
6199 QQQ.Open_mva050 50 Day MA
6203 QQQ.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6205 QQQ.High_SmoothDer Derivative of Smoothed
6208 QQQ.High_mva200 200 Day MA
6209 QQQ.High_mva050 50 Day MA
6213 QQQ.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6215 QQQ.Low_SmoothDer Derivative of Smoothed
6218 QQQ.Low_mva200 200 Day MA
6219 QQQ.Low_mva050 50 Day MA
6223 QQQ.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6225 QQQ.Close_SmoothDer Derivative of Smoothed
6228 QQQ.Close_mva200 200 Day MA
6229 QQQ.Close_mva050 50 Day MA
6243 QQQ.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6245 QQQ.Adjusted_SmoothDer Derivative of Smoothed
6248 QQQ.Adjusted_mva200 200 Day MA
6249 QQQ.Adjusted_mva050 50 Day MA
6295 HYMB.Volume_SmoothDer Derivative of Smoothed
6296 HYMB.Volume_Log Log of
6308 HYMB.Adjusted_mva200 200 Day MA
6316 GOLD.Open_Log Log of
6356 GOLD.Volume_Log Log of
6370 BKR.Open_YoY Year over Year
6374 BKR.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
6376 BKR.Open_Log Log of
6378 BKR.Open_mva200 200 Day MA
6380 BKR.High_YoY Year over Year
6384 BKR.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
6386 BKR.High_Log Log of
6388 BKR.High_mva200 200 Day MA
6390 BKR.Low_YoY Year over Year
6394 BKR.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
6396 BKR.Low_Log Log of
6398 BKR.Low_mva200 200 Day MA
6400 BKR.Close_YoY Year over Year
6404 BKR.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
6406 BKR.Close_Log Log of
6408 BKR.Close_mva200 200 Day MA
6413 BKR.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6415 BKR.Volume_SmoothDer Derivative of Smoothed
6416 BKR.Volume_Log Log of
6420 BKR.Adjusted_YoY Year over Year
6424 BKR.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
6426 BKR.Adjusted_Log Log of
6428 BKR.Adjusted_mva200 200 Day MA
6430 SLB.Open_YoY Year over Year
6437 SLB.Open_mva365 365 Day MA
6440 SLB.High_YoY Year over Year
6447 SLB.High_mva365 365 Day MA
6450 SLB.Low_YoY Year over Year
6457 SLB.Low_mva365 365 Day MA
6460 SLB.Close_YoY Year over Year
6467 SLB.Close_mva365 365 Day MA
6473 SLB.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6475 SLB.Volume_SmoothDer Derivative of Smoothed
6480 SLB.Adjusted_YoY Year over Year
6487 SLB.Adjusted_mva365 365 Day MA
6496 HAL.Open_Log Log of
6501 HAL.High_YoY4 4 Year over 4 Year
6511 HAL.Low_YoY4 4 Year over 4 Year
6521 HAL.Close_YoY4 4 Year over 4 Year
6532 HAL.Volume_YoY5 5 Year over 5 Year
6533 HAL.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6536 HAL.Volume_Log Log of
6541 HAL.Adjusted_YoY4 4 Year over 4 Year
6555 IP.Open_SmoothDer Derivative of Smoothed
6556 IP.Open_Log Log of
6565 IP.High_SmoothDer Derivative of Smoothed
6575 IP.Low_SmoothDer Derivative of Smoothed
6585 IP.Close_SmoothDer Derivative of Smoothed
6593 IP.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6605 IP.Adjusted_SmoothDer Derivative of Smoothed
6668 PKG.Adjusted_mva200 200 Day MA
6713 UPS.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6715 UPS.Volume_SmoothDer Derivative of Smoothed
6734 FDX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
6735 FDX.Open_SmoothDer Derivative of Smoothed
6736 FDX.Open_Log Log of
6738 FDX.Open_mva200 200 Day MA
6739 FDX.Open_mva050 50 Day MA
6744 FDX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
6745 FDX.High_SmoothDer Derivative of Smoothed
6746 FDX.High_Log Log of
6748 FDX.High_mva200 200 Day MA
6749 FDX.High_mva050 50 Day MA
6754 FDX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
6755 FDX.Low_SmoothDer Derivative of Smoothed
6756 FDX.Low_Log Log of
6758 FDX.Low_mva200 200 Day MA
6759 FDX.Low_mva050 50 Day MA
6764 FDX.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
6765 FDX.Close_SmoothDer Derivative of Smoothed
6766 FDX.Close_Log Log of
6768 FDX.Close_mva200 200 Day MA
6769 FDX.Close_mva050 50 Day MA
6773 FDX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6775 FDX.Volume_SmoothDer Derivative of Smoothed
6784 FDX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
6785 FDX.Adjusted_SmoothDer Derivative of Smoothed
6786 FDX.Adjusted_Log Log of
6787 FDX.Adjusted_mva365 365 Day MA
6788 FDX.Adjusted_mva200 200 Day MA
6789 FDX.Adjusted_mva050 50 Day MA
6796 T.Open_Log Log of
6833 T.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6835 T.Volume_SmoothDer Derivative of Smoothed
6855 VZ.Open_SmoothDer Derivative of Smoothed
6865 VZ.High_SmoothDer Derivative of Smoothed
6875 VZ.Low_SmoothDer Derivative of Smoothed
6885 VZ.Close_SmoothDer Derivative of Smoothed
6893 VZ.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6905 VZ.Adjusted_SmoothDer Derivative of Smoothed
6910 ISMMANPMI_YoY Institute of Supply Managment PMI Composite Index Year over Year
6911 ISMMANPMI_YoY4 Institute of Supply Managment PMI Composite Index 4 Year over 4 Year
6916 ISMMANPMI_Log Log of Institute of Supply Managment PMI Composite Index
6918 ISMMANPMI_mva200 Institute of Supply Managment PMI Composite Index 200 Day MA
6919 ISMMANPMI_mva050 Institute of Supply Managment PMI Composite Index 50 Day MA
6923 MULTPLSP500PERATIOMONTH_Smooth Savitsky-Golay Smoothed (p=3, n=365) S&P 500 TTM P/E
6926 MULTPLSP500PERATIOMONTH_Log Log of S&P 500 TTM P/E
6927 MULTPLSP500PERATIOMONTH_mva365 S&P 500 TTM P/E 365 Day MA
6928 MULTPLSP500PERATIOMONTH_mva200 S&P 500 TTM P/E 200 Day MA
6929 MULTPLSP500PERATIOMONTH_mva050 S&P 500 TTM P/E 50 Day MA
6936 MULTPLSP500SALESQUARTER_Log Log of S&P 500 TTM Sales (Not Inflation Adjusted)
6937 MULTPLSP500SALESQUARTER_mva365 S&P 500 TTM Sales (Not Inflation Adjusted) 365 Day MA
6938 MULTPLSP500SALESQUARTER_mva200 S&P 500 TTM Sales (Not Inflation Adjusted) 200 Day MA
6939 MULTPLSP500SALESQUARTER_mva050 S&P 500 TTM Sales (Not Inflation Adjusted) 50 Day MA
6957 MULTPLSP500DIVMONTH_mva365 S&P 500 Dividend by Month (Inflation Adjusted) 365 Day MA
6958 MULTPLSP500DIVMONTH_mva200 S&P 500 Dividend by Month (Inflation Adjusted) 200 Day MA
6960 CHRISCMEHG1_YoY Copper Futures, Continuous Contract #1 (HG1) (Front Month) Year over Year
6966 CHRISCMEHG1_Log Log of Copper Futures, Continuous Contract #1 (HG1) (Front Month)
6967 CHRISCMEHG1_mva365 Copper Futures, Continuous Contract #1 (HG1) (Front Month) 365 Day MA
6968 CHRISCMEHG1_mva200 Copper Futures, Continuous Contract #1 (HG1) (Front Month) 200 Day MA
6969 CHRISCMEHG1_mva050 Copper Futures, Continuous Contract #1 (HG1) (Front Month) 50 Day MA
6970 WWDIWLDISAIRGOODMTK1_YoY Air transport, freight Year over Year
6971 WWDIWLDISAIRGOODMTK1_YoY4 Air transport, freight 4 Year over 4 Year
6976 WWDIWLDISAIRGOODMTK1_Log Log of Air transport, freight
6977 WWDIWLDISAIRGOODMTK1_mva365 Air transport, freight 365 Day MA
6978 WWDIWLDISAIRGOODMTK1_mva200 Air transport, freight 200 Day MA
6979 WWDIWLDISAIRGOODMTK1_mva050 Air transport, freight 50 Day MA
6980 LBMAGOLD.USD_AM_YoY Year over Year
6982 LBMAGOLD.USD_AM_YoY5 5 Year over 5 Year
6987 LBMAGOLD.USD_AM_mva365 365 Day MA
6988 LBMAGOLD.USD_AM_mva200 200 Day MA
6990 LBMAGOLD.USD_PM_YoY Year over Year
6992 LBMAGOLD.USD_PM_YoY5 5 Year over 5 Year
6997 LBMAGOLD.USD_PM_mva365 365 Day MA
6998 LBMAGOLD.USD_PM_mva200 200 Day MA
7007 LBMAGOLD.GBP_AM_mva365 365 Day MA
7008 LBMAGOLD.GBP_AM_mva200 200 Day MA
7017 LBMAGOLD.GBP_PM_mva365 365 Day MA
7018 LBMAGOLD.GBP_PM_mva200 200 Day MA
7027 LBMAGOLD.EURO_AM_mva365 365 Day MA
7028 LBMAGOLD.EURO_AM_mva200 200 Day MA
7037 LBMAGOLD.EURO_PM_mva365 365 Day MA
7038 LBMAGOLD.EURO_PM_mva200 200 Day MA
7046 PETA103600001M_Log Log of U.S. Total Gasoline Retail Sales by Refiners, Monthly
7048 PETA103600001M_mva200 U.S. Total Gasoline Retail Sales by Refiners, Monthly 200 Day MA
7049 PETA103600001M_mva050 U.S. Total Gasoline Retail Sales by Refiners, Monthly 50 Day MA
7055 PETA123600001M_SmoothDer Derivative of Smoothed U.S. Regular Gasoline Retail Sales by Refiners, Monthly
7056 PETA123600001M_Log Log of U.S. Regular Gasoline Retail Sales by Refiners, Monthly
7057 PETA123600001M_mva365 U.S. Regular Gasoline Retail Sales by Refiners, Monthly 365 Day MA
7058 PETA123600001M_mva200 U.S. Regular Gasoline Retail Sales by Refiners, Monthly 200 Day MA
7059 PETA123600001M_mva050 U.S. Regular Gasoline Retail Sales by Refiners, Monthly 50 Day MA
7060 PETA143B00001M_YoY U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly Year over Year
7061 PETA143B00001M_YoY4 U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 4 Year over 4 Year
7062 PETA143B00001M_YoY5 U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 5 Year over 5 Year
7066 PETA143B00001M_Log Log of U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly
7067 PETA143B00001M_mva365 U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 365 Day MA
7068 PETA143B00001M_mva200 U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 200 Day MA
7069 PETA143B00001M_mva050 U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 50 Day MA
7070 PETA133B00001M_YoY U.S. Premium Gasoline Bulk Sales (Volume) by Refiners, Monthly Year over Year
7076 PETA133B00001M_Log Log of U.S. Premium Gasoline Bulk Sales (Volume) by Refiners, Monthly
7078 PETA133B00001M_mva200 U.S. Premium Gasoline Bulk Sales (Volume) by Refiners, Monthly 200 Day MA
7079 PETA133B00001M_mva050 U.S. Premium Gasoline Bulk Sales (Volume) by Refiners, Monthly 50 Day MA
7081 TOTALOGNRPUSM_YoY4 Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly 4 Year over 4 Year
7091 TOTALPANRPUSM_YoY4 Crude Oil Rotary Rigs in Operation, Monthly 4 Year over 4 Year
7101 TOTALNGNRPUSM_YoY4 Natural Gas Rotary Rigs in Operation, Monthly 4 Year over 4 Year
7111 BKRTotal_YoY4 Total Rig Count 4 Year over 4 Year
7115 BKRTotal_SmoothDer Derivative of Smoothed Total Rig Count
7116 BKRTotal_Log Log of Total Rig Count
7117 BKRTotal_mva365 Total Rig Count 365 Day MA
7118 BKRTotal_mva200 Total Rig Count 200 Day MA
7119 BKRTotal_mva050 Total Rig Count 50 Day MA
7125 BKRGas_SmoothDer Derivative of Smoothed Gas Rig Count
7126 BKRGas_Log Log of Gas Rig Count
7127 BKRGas_mva365 Gas Rig Count 365 Day MA
7128 BKRGas_mva200 Gas Rig Count 200 Day MA
7129 BKRGas_mva050 Gas Rig Count 50 Day MA
7131 BKROil_YoY4 Oil Rig Count 4 Year over 4 Year
7135 BKROil_SmoothDer Derivative of Smoothed Oil Rig Count
7136 BKROil_Log Log of Oil Rig Count
7137 BKROil_mva365 Oil Rig Count 365 Day MA
7138 BKROil_mva200 Oil Rig Count 200 Day MA
7139 BKROil_mva050 Oil Rig Count 50 Day MA
7140 FARMINCOME_YoY Net Farm Income Year over Year
7141 FARMINCOME_YoY4 Net Farm Income 4 Year over 4 Year
7146 FARMINCOME_Log Log of Net Farm Income
7147 FARMINCOME_mva365 Net Farm Income 365 Day MA
7148 FARMINCOME_mva200 Net Farm Income 200 Day MA
7149 FARMINCOME_mva050 Net Farm Income 50 Day MA
7153 OPEARNINGSPERSHARE_Smooth Savitsky-Golay Smoothed (p=3, n=365) Operating Earnings per Share
7156 OPEARNINGSPERSHARE_Log Log of Operating Earnings per Share
7157 OPEARNINGSPERSHARE_mva365 Operating Earnings per Share 365 Day MA
7158 OPEARNINGSPERSHARE_mva200 Operating Earnings per Share 200 Day MA
7159 OPEARNINGSPERSHARE_mva050 Operating Earnings per Share 50 Day MA
7163 AREARNINGSPERSHARE_Smooth Savitsky-Golay Smoothed (p=3, n=365) As-Reported Earnings per Share
7165 AREARNINGSPERSHARE_SmoothDer Derivative of Smoothed As-Reported Earnings per Share
7166 AREARNINGSPERSHARE_Log Log of As-Reported Earnings per Share
7176 CASHDIVIDENDSPERSHR_Log Log of Cash Dividends per Share
7177 CASHDIVIDENDSPERSHR_mva365 Cash Dividends per Share 365 Day MA
7178 CASHDIVIDENDSPERSHR_mva200 Cash Dividends per Share 200 Day MA
7179 CASHDIVIDENDSPERSHR_mva050 Cash Dividends per Share 50 Day MA
7186 SALESPERSHR_Log Log of Sales per Share
7187 SALESPERSHR_mva365 Sales per Share 365 Day MA
7188 SALESPERSHR_mva200 Sales per Share 200 Day MA
7189 SALESPERSHR_mva050 Sales per Share 50 Day MA
7190 BOOKVALPERSHR_YoY Book value per Share Year over Year
7196 BOOKVALPERSHR_Log Log of Book value per Share
7197 BOOKVALPERSHR_mva365 Book value per Share 365 Day MA
7198 BOOKVALPERSHR_mva200 Book value per Share 200 Day MA
7199 BOOKVALPERSHR_mva050 Book value per Share 50 Day MA
7206 CAPEXPERSHR_Log Log of Cap ex per Share
7207 CAPEXPERSHR_mva365 Cap ex per Share 365 Day MA
7208 CAPEXPERSHR_mva200 Cap ex per Share 200 Day MA
7209 CAPEXPERSHR_mva050 Cap ex per Share 50 Day MA
7210 PRICE_YoY Price Year over Year
7216 PRICE_Log Log of Price
7218 PRICE_mva200 Price 200 Day MA
7219 PRICE_mva050 Price 50 Day MA
7220 OPEARNINGSTTM_YoY TTM Operating Earnings Year over Year
7223 OPEARNINGSTTM_Smooth Savitsky-Golay Smoothed (p=3, n=365) TTM Operating Earnings
7225 OPEARNINGSTTM_SmoothDer Derivative of Smoothed TTM Operating Earnings
7226 OPEARNINGSTTM_Log Log of TTM Operating Earnings
7230 AREARNINGSTTM_YoY TTM Reported Earnings Year over Year
7233 AREARNINGSTTM_Smooth Savitsky-Golay Smoothed (p=3, n=365) TTM Reported Earnings
7235 AREARNINGSTTM_SmoothDer Derivative of Smoothed TTM Reported Earnings
7236 AREARNINGSTTM_Log Log of TTM Reported Earnings
7243 FINRAMarginDebt_Smooth Savitsky-Golay Smoothed (p=3, n=365) Margin Debt
7245 FINRAMarginDebt_SmoothDer Derivative of Smoothed Margin Debt
7246 FINRAMarginDebt_Log Log of Margin Debt
7249 FINRAMarginDebt_mva050 Margin Debt 50 Day MA
7250 FINRAFreeCreditMargin_YoY Free Credit Balances in Customers’ Securities Margin Accounts Year over Year
7255 FINRAFreeCreditMargin_SmoothDer Derivative of Smoothed Free Credit Balances in Customers’ Securities Margin Accounts
7260 OCCEquityVolume_YoY Equity Options Volume Year over Year
7266 OCCEquityVolume_Log Log of Equity Options Volume
7267 OCCEquityVolume_mva365 Equity Options Volume 365 Day MA
7268 OCCEquityVolume_mva200 Equity Options Volume 200 Day MA
7269 OCCEquityVolume_mva050 Equity Options Volume 50 Day MA
7270 OCCNonEquityVolume_YoY Non-Equity Options Volume Year over Year
7276 OCCNonEquityVolume_Log Log of Non-Equity Options Volume
7277 OCCNonEquityVolume_mva365 Non-Equity Options Volume 365 Day MA
7278 OCCNonEquityVolume_mva200 Non-Equity Options Volume 200 Day MA
7279 OCCNonEquityVolume_mva050 Non-Equity Options Volume 50 Day MA
7285 RSALESAGG_SmoothDer Derivative of Smoothed Real Retail and Food Services Sales (RRSFS and RSALES)
7291 BUSLOANS.minus.BUSLOANSNSA_YoY4 Business Loans (Montlhy) SA - NSA 4 Year over 4 Year
7295 BUSLOANS.minus.BUSLOANSNSA_SmoothDer Derivative of Smoothed Business Loans (Montlhy) SA - NSA
7296 BUSLOANS.minus.BUSLOANSNSA_Log Log of Business Loans (Montlhy) SA - NSA
7301 BUSLOANS.minus.BUSLOANSNSA.by.GDP_YoY4 Business Loans (Montlhy) SA - NSA divided by GDP 4 Year over 4 Year
7305 BUSLOANS.minus.BUSLOANSNSA.by.GDP_SmoothDer Derivative of Smoothed Business Loans (Montlhy) SA - NSA divided by GDP
7306 BUSLOANS.minus.BUSLOANSNSA.by.GDP_Log Log of Business Loans (Montlhy) SA - NSA divided by GDP
7315 BUSLOANS.by.GDP_SmoothDer Derivative of Smoothed Business Loans Normalized by GDP
7323 BUSLOANS.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Monthly, SA) Adjusted Interest Burdens
7327 BUSLOANS.INTEREST_mva365 Business Loans (Monthly, SA) Adjusted Interest Burdens 365 Day MA
7329 BUSLOANS.INTEREST_mva050 Business Loans (Monthly, SA) Adjusted Interest Burdens 50 Day MA
7333 BUSLOANS.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP
7335 BUSLOANS.INTEREST.by.GDP_SmoothDer Derivative of Smoothed Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP
7337 BUSLOANS.INTEREST.by.GDP_mva365 Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP 365 Day MA
7339 BUSLOANS.INTEREST.by.GDP_mva050 Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP 50 Day MA
7341 BUSLOANSNSA.by.GDP_YoY4 Business Loans Normalized by GDP 4 Year over 4 Year
7373 TOTCINSA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Weekly, NSA) Adjusted Interest Burdens
7377 TOTCINSA.INTEREST_mva365 Business Loans (Weekly, NSA) Adjusted Interest Burdens 365 Day MA
7383 TOTCINSA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP
7387 TOTCINSA.INTEREST.by.GDP_mva365 Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP 365 Day MA
7393 W875RX1.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Personal Income Normalized by GDP
7395 W875RX1.by.GDP_SmoothDer Derivative of Smoothed Real Personal Income Normalized by GDP
7396 W875RX1.by.GDP_Log Log of Real Personal Income Normalized by GDP
7399 W875RX1.by.GDP_mva050 Real Personal Income Normalized by GDP 50 Day MA
7400 A065RC1A027NBEA.by.GDP_YoY Personal Income (NSA) Normalized by GDP Year over Year
7405 A065RC1A027NBEA.by.GDP_SmoothDer Derivative of Smoothed Personal Income (NSA) Normalized by GDP
7406 A065RC1A027NBEA.by.GDP_Log Log of Personal Income (NSA) Normalized by GDP
7413 PI.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Personal Income (SA) Normalized by GDP
7415 PI.by.GDP_SmoothDer Derivative of Smoothed Personal Income (SA) Normalized by GDP
7416 PI.by.GDP_Log Log of Personal Income (SA) Normalized by GDP
7417 PI.by.GDP_mva365 Personal Income (SA) Normalized by GDP 365 Day MA
7418 PI.by.GDP_mva200 Personal Income (SA) Normalized by GDP 200 Day MA
7419 PI.by.GDP_mva050 Personal Income (SA) Normalized by GDP 50 Day MA
7420 A053RC1Q027SBEA.by.GDP_YoY National income: Corporate profits before tax (without IVA and CCAdj) Normalized by GDP Year over Year
7425 A053RC1Q027SBEA.by.GDP_SmoothDer Derivative of Smoothed National income: Corporate profits before tax (without IVA and CCAdj) Normalized by GDP
7426 A053RC1Q027SBEA.by.GDP_Log Log of National income: Corporate profits before tax (without IVA and CCAdj) Normalized by GDP
7430 CPROFIT.by.GDP_YoY National income: Corporate profits before tax (with IVA and CCAdj) Normalized by GDP Year over Year
7435 CPROFIT.by.GDP_SmoothDer Derivative of Smoothed National income: Corporate profits before tax (with IVA and CCAdj) Normalized by GDP
7436 CPROFIT.by.GDP_Log Log of National income: Corporate profits before tax (with IVA and CCAdj) Normalized by GDP
7443 CONSUMERNSA.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Consumer Loans Not Seasonally Adjusted divided by GDP
7445 CONSUMERNSA.by.GDP_SmoothDer Derivative of Smoothed Consumer Loans Not Seasonally Adjusted divided by GDP
7446 CONSUMERNSA.by.GDP_Log Log of Consumer Loans Not Seasonally Adjusted divided by GDP
7447 CONSUMERNSA.by.GDP_mva365 Consumer Loans Not Seasonally Adjusted divided by GDP 365 Day MA
7449 CONSUMERNSA.by.GDP_mva050 Consumer Loans Not Seasonally Adjusted divided by GDP 50 Day MA
7453 RREACBM027NBOG.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Monthly, NSA) divided by GDP
7455 RREACBM027NBOG.by.GDP_SmoothDer Derivative of Smoothed Residental Real Estate Loans (Monthly, NSA) divided by GDP
7456 RREACBM027NBOG.by.GDP_Log Log of Residental Real Estate Loans (Monthly, NSA) divided by GDP
7457 RREACBM027NBOG.by.GDP_mva365 Residental Real Estate Loans (Monthly, NSA) divided by GDP 365 Day MA
7458 RREACBM027NBOG.by.GDP_mva200 Residental Real Estate Loans (Monthly, NSA) divided by GDP 200 Day MA
7459 RREACBM027NBOG.by.GDP_mva050 Residental Real Estate Loans (Monthly, NSA) divided by GDP 50 Day MA
7461 RREACBM027SBOG.by.GDP_YoY4 Residental Real Estate Loans (Monthly, SA) divided by GDP 4 Year over 4 Year
7462 RREACBM027SBOG.by.GDP_YoY5 Residental Real Estate Loans (Monthly, SA) divided by GDP 5 Year over 5 Year
7466 RREACBM027SBOG.by.GDP_Log Log of Residental Real Estate Loans (Monthly, SA) divided by GDP
7467 RREACBM027SBOG.by.GDP_mva365 Residental Real Estate Loans (Monthly, SA) divided by GDP 365 Day MA
7468 RREACBM027SBOG.by.GDP_mva200 Residental Real Estate Loans (Monthly, SA) divided by GDP 200 Day MA
7469 RREACBM027SBOG.by.GDP_mva050 Residental Real Estate Loans (Monthly, SA) divided by GDP 50 Day MA
7477 RREACBW027SBOG.by.GDP_mva365 Residental Real Estate Loans (Weekly, SA) divided by GDP 365 Day MA
7478 RREACBW027SBOG.by.GDP_mva200 Residental Real Estate Loans (Weekly, SA) divided by GDP 200 Day MA
7483 RREACBW027NBOG.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Weekly, NSA) divided by GDP
7485 RREACBW027NBOG.by.GDP_SmoothDer Derivative of Smoothed Residental Real Estate Loans (Weekly, NSA) divided by GDP
7487 RREACBW027NBOG.by.GDP_mva365 Residental Real Estate Loans (Weekly, NSA) divided by GDP 365 Day MA
7488 RREACBW027NBOG.by.GDP_mva200 Residental Real Estate Loans (Weekly, NSA) divided by GDP 200 Day MA
7493 UMDMNO.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Durable Goods (Monthly, NSA) divided by GDP
7495 UMDMNO.by.GDP_SmoothDer Derivative of Smoothed Durable Goods (Monthly, NSA) divided by GDP
7498 UMDMNO.by.GDP_mva200 Durable Goods (Monthly, NSA) divided by GDP 200 Day MA
7500 DGORDER.by.GDP_YoY Durable Goods (Monthly, NSA) divided by GDP Year over Year
7503 DGORDER.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Durable Goods (Monthly, NSA) divided by GDP
7505 DGORDER.by.GDP_SmoothDer Derivative of Smoothed Durable Goods (Monthly, NSA) divided by GDP
7506 DGORDER.by.GDP_Log Log of Durable Goods (Monthly, NSA) divided by GDP
7508 DGORDER.by.GDP_mva200 Durable Goods (Monthly, NSA) divided by GDP 200 Day MA
7509 DGORDER.by.GDP_mva050 Durable Goods (Monthly, NSA) divided by GDP 50 Day MA
7510 ASHMA.by.GDP_YoY Home Mortgages (Quarterly, NSA) divided by GDP Year over Year
7511 ASHMA.by.GDP_YoY4 Home Mortgages (Quarterly, NSA) divided by GDP 4 Year over 4 Year
7512 ASHMA.by.GDP_YoY5 Home Mortgages (Quarterly, NSA) divided by GDP 5 Year over 5 Year
7513 ASHMA.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Home Mortgages (Quarterly, NSA) divided by GDP
7515 ASHMA.by.GDP_SmoothDer Derivative of Smoothed Home Mortgages (Quarterly, NSA) divided by GDP
7516 ASHMA.by.GDP_Log Log of Home Mortgages (Quarterly, NSA) divided by GDP
7523 ASHMA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
7525 ASHMA.INTEREST_SmoothDer Derivative of Smoothed Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
7526 ASHMA.INTEREST_Log Log of Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
7527 ASHMA.INTEREST_mva365 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 365 Day MA
7529 ASHMA.INTEREST_mva050 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 50 Day MA
7533 ASHMA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP
7535 ASHMA.INTEREST.by.GDP_SmoothDer Derivative of Smoothed Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP
7536 ASHMA.INTEREST.by.GDP_Log Log of Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP
7537 ASHMA.INTEREST.by.GDP_mva365 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP 365 Day MA
7539 ASHMA.INTEREST.by.GDP_mva050 Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP 50 Day MA
7541 CONSUMERNSA.INTEREST_YoY4 Consumer Loans (Not Seasonally Adjusted) Interest Burdens 4 Year over 4 Year
7543 CONSUMERNSA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Consumer Loans (Not Seasonally Adjusted) Interest Burdens
7546 CONSUMERNSA.INTEREST_Log Log of Consumer Loans (Not Seasonally Adjusted) Interest Burdens
7547 CONSUMERNSA.INTEREST_mva365 Consumer Loans (Not Seasonally Adjusted) Interest Burdens 365 Day MA
7548 CONSUMERNSA.INTEREST_mva200 Consumer Loans (Not Seasonally Adjusted) Interest Burdens 200 Day MA
7549 CONSUMERNSA.INTEREST_mva050 Consumer Loans (Not Seasonally Adjusted) Interest Burdens 50 Day MA
7551 CONSUMERNSA.INTEREST.by.GDP_YoY4 Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP 4 Year over 4 Year
7552 CONSUMERNSA.INTEREST.by.GDP_YoY5 Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP 5 Year over 5 Year
7553 CONSUMERNSA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP
7556 CONSUMERNSA.INTEREST.by.GDP_Log Log of Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP
7557 CONSUMERNSA.INTEREST.by.GDP_mva365 Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP 365 Day MA
7558 CONSUMERNSA.INTEREST.by.GDP_mva200 Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP 200 Day MA
7559 CONSUMERNSA.INTEREST.by.GDP_mva050 Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP 50 Day MA
7563 TOTLNNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA)
7566 TOTLNNSA_Log Log of Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA)
7567 TOTLNNSA_mva365 Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA) 365 Day MA
7568 TOTLNNSA_mva200 Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA) 200 Day MA
7569 TOTLNNSA_mva050 Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA) 50 Day MA
7573 TOTLNNSA.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted divided by GDP
7576 TOTLNNSA.by.GDP_Log Log of Total Loans Not Seasonally Adjusted divided by GDP
7577 TOTLNNSA.by.GDP_mva365 Total Loans Not Seasonally Adjusted divided by GDP 365 Day MA
7578 TOTLNNSA.by.GDP_mva200 Total Loans Not Seasonally Adjusted divided by GDP 200 Day MA
7579 TOTLNNSA.by.GDP_mva050 Total Loans Not Seasonally Adjusted divided by GDP 50 Day MA
7583 TOTLNNSA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted Interest Burdens
7587 TOTLNNSA.INTEREST_mva365 Total Loans Not Seasonally Adjusted Interest Burdens 365 Day MA
7589 TOTLNNSA.INTEREST_mva050 Total Loans Not Seasonally Adjusted Interest Burdens 50 Day MA
7593 TOTLNNSA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP
7595 TOTLNNSA.INTEREST.by.GDP_SmoothDer Derivative of Smoothed Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP
7597 TOTLNNSA.INTEREST.by.GDP_mva365 Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP 365 Day MA
7599 TOTLNNSA.INTEREST.by.GDP_mva050 Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP 50 Day MA
7610 EXCSRESNW.by.GDP_YoY Excess Reserves of Depository Institutions Divided by GDP Year over Year
7615 EXCSRESNW.by.GDP_SmoothDer Derivative of Smoothed Excess Reserves of Depository Institutions Divided by GDP
7616 EXCSRESNW.by.GDP_Log Log of Excess Reserves of Depository Institutions Divided by GDP
7625 WLRRAL.by.GDP_SmoothDer Derivative of Smoothed Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) Divided by GDP
7635 SOFR99.minus.SOFR1_SmoothDer Derivative of Smoothed Secured Overnight Financing Rate: 99th Percentile - 1st Percentile
7646 EXPCH.minus.IMPCH_Log Log of U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis)
7647 EXPCH.minus.IMPCH_mva365 U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis) 365 Day MA
7656 EXPMX.minus.IMPMX_Log Log of
7663 SRPSABSNNCB.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP
7666 SRPSABSNNCB.by.GDP_Log Log of Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP
7667 SRPSABSNNCB.by.GDP_mva365 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP 365 Day MA
7668 SRPSABSNNCB.by.GDP_mva200 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP 200 Day MA
7669 SRPSABSNNCB.by.GDP_mva050 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP 50 Day MA
7676 ASTLL.by.GDP_Log Log of All sectors; total loans; liability, Level (NSA) Divided by GDP
7678 ASTLL.by.GDP_mva200 All sectors; total loans; liability, Level (NSA) Divided by GDP 200 Day MA
7679 ASTLL.by.GDP_mva050 All sectors; total loans; liability, Level (NSA) Divided by GDP 50 Day MA
7686 ASFMA.by.GDP_Log Log of All sectors; farm mortgages; asset, Level (NSA) Divided by GDP
7687 ASFMA.by.GDP_mva365 All sectors; farm mortgages; asset, Level (NSA) Divided by GDP 365 Day MA
7688 ASFMA.by.GDP_mva200 All sectors; farm mortgages; asset, Level (NSA) Divided by GDP 200 Day MA
7689 ASFMA.by.GDP_mva050 All sectors; farm mortgages; asset, Level (NSA) Divided by GDP 50 Day MA
7692 ASFMA.by.ASTLL_YoY5 All sectors; total loans Divided by farm mortgages 5 Year over 5 Year
7696 ASFMA.by.ASTLL_Log Log of All sectors; total loans Divided by farm mortgages
7697 ASFMA.by.ASTLL_mva365 All sectors; total loans Divided by farm mortgages 365 Day MA
7698 ASFMA.by.ASTLL_mva200 All sectors; total loans Divided by farm mortgages 200 Day MA
7699 ASFMA.by.ASTLL_mva050 All sectors; total loans Divided by farm mortgages 50 Day MA
7703 ASFMA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
7706 ASFMA.INTEREST_Log Log of Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
7707 ASFMA.INTEREST_mva365 Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 365 Day MA
7709 ASFMA.INTEREST_mva050 Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 50 Day MA
7713 ASFMA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
7715 ASFMA.INTEREST.by.GDP_SmoothDer Derivative of Smoothed Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
7716 ASFMA.INTEREST.by.GDP_Log Log of Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
7717 ASFMA.INTEREST.by.GDP_mva365 Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP 365 Day MA
7719 ASFMA.INTEREST.by.GDP_mva050 Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP 50 Day MA
7720 FARMINCOME.by.GDP_YoY Farm Income (Annual, NSA) Divided by GDP Year over Year
7721 FARMINCOME.by.GDP_YoY4 Farm Income (Annual, NSA) Divided by GDP 4 Year over 4 Year
7725 FARMINCOME.by.GDP_SmoothDer Derivative of Smoothed Farm Income (Annual, NSA) Divided by GDP
7726 FARMINCOME.by.GDP_Log Log of Farm Income (Annual, NSA) Divided by GDP
7732 BOGMBASE.by.GDP_YoY5 BOGMBASE Divided by GDP 5 Year over 5 Year
7738 BOGMBASE.by.GDP_mva200 BOGMBASE Divided by GDP 200 Day MA
7745 WALCL.by.GDP_SmoothDer Derivative of Smoothed All Federal Reserve Banks: Total Assets Divided by GDP
7750 ECBASSETS.by.EUNNGDP_YoY Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP Year over Year
7751 ECBASSETS.by.EUNNGDP_YoY4 Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP 4 Year over 4 Year
7755 ECBASSETS.by.EUNNGDP_SmoothDer Derivative of Smoothed Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP
7756 ECBASSETS.by.EUNNGDP_Log Log of Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP
7766 DGS30TO10_Log Log of Yield Curve, 30 and 10 Year Treasury (DGS30-DGS10)
7770 DGS10TO1_YoY Yield Curve, 10 and 1 Year Treasury (DGS10-DGS1) Year over Year
7775 DGS10TO1_SmoothDer Derivative of Smoothed Yield Curve, 10 and 1 Year Treasury (DGS10-DGS1)
7776 DGS10TO1_Log Log of Yield Curve, 10 and 1 Year Treasury (DGS10-DGS1)
7785 DGS10TO2_SmoothDer Derivative of Smoothed Yield Curve, 10 and 2 Year Treasury (DGS10-DGS2)
7786 DGS10TO2_Log Log of Yield Curve, 10 and 2 Year Treasury (DGS10-DGS2)
7795 DGS10TOTB3MS_SmoothDer Derivative of Smoothed Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS)
7796 DGS10TOTB3MS_Log Log of Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS)
7805 DGS10TODTB3_SmoothDer Derivative of Smoothed Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3)
7806 DGS10TODTB3_Log Log of Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3)
7823 LNU03000000BYPOPTHM_Smooth Savitsky-Golay Smoothed (p=3, n=365) Unemployment level (NSA) / Population
7825 LNU03000000BYPOPTHM_SmoothDer Derivative of Smoothed Unemployment level (NSA) / Population
7828 LNU03000000BYPOPTHM_mva200 Unemployment level (NSA) / Population 200 Day MA
7833 UNEMPLOYBYPOPTHM_Smooth Savitsky-Golay Smoothed (p=3, n=365) Unemployment level, seasonally adjusted / Population
7835 UNEMPLOYBYPOPTHM_SmoothDer Derivative of Smoothed Unemployment level, seasonally adjusted / Population
7845 NPPTTLBYPOPTHM_SmoothDer Derivative of Smoothed ADP Private Employment / Population
7852 U6toU3_YoY5 U6RATE minums UNRATE 5 Year over 5 Year
7855 U6toU3_SmoothDer Derivative of Smoothed U6RATE minums UNRATE
7856 U6toU3_Log Log of U6RATE minums UNRATE
7858 U6toU3_mva200 U6RATE minums UNRATE 200 Day MA
7859 U6toU3_mva050 U6RATE minums UNRATE 50 Day MA
7863 CHRISCMEHG1.by.PPIACO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Copper, $/lb, Normalized by commodities producer price index
7866 CHRISCMEHG1.by.PPIACO_Log Log of Copper, $/lb, Normalized by commodities producer price index
7867 CHRISCMEHG1.by.PPIACO_mva365 Copper, $/lb, Normalized by commodities producer price index 365 Day MA
7868 CHRISCMEHG1.by.PPIACO_mva200 Copper, $/lb, Normalized by commodities producer price index 200 Day MA
7869 CHRISCMEHG1.by.PPIACO_mva050 Copper, $/lb, Normalized by commodities producer price index 50 Day MA
7870 CHRISCMEHG1.by.CPIAUCSL_YoY Copper, $/lb, Normalized by consumer price index Year over Year
7885 DCOILBRENTEU.by.PPIACO_SmoothDer Derivative of Smoothed Crude Oil - Brent, $/bbl, Normalized by producer price index c.o.
7895 DCOILWTICO.by.PPIACO_SmoothDer Derivative of Smoothed Crude Oil - WTI, $/bbl, Normalized by producer price index c.o.
7896 DCOILWTICO.by.PPIACO_Log Log of Crude Oil - WTI, $/bbl, Normalized by producer price index c.o.
7902 LBMAGOLD.USD_PM.by.PPIACO_YoY5 Gold, USD PM/Troy Ounce, Normalized by commodities producer price index 5 Year over 5 Year
7907 LBMAGOLD.USD_PM.by.PPIACO_mva365 Gold, USD PM/Troy Ounce, Normalized by commodities producer price index 365 Day MA
7908 LBMAGOLD.USD_PM.by.PPIACO_mva200 Gold, USD PM/Troy Ounce, Normalized by commodities producer price index 200 Day MA
7910 LBMAGOLD.USD_PM.by.CPIAUCSL_YoY Gold, USD/Troy OUnce, Normalized by consumer price index Year over Year
7912 LBMAGOLD.USD_PM.by.CPIAUCSL_YoY5 Gold, USD/Troy OUnce, Normalized by consumer price index 5 Year over 5 Year
7918 LBMAGOLD.USD_PM.by.CPIAUCSL_mva200 Gold, USD/Troy OUnce, Normalized by consumer price index 200 Day MA
7920 LBMAGOLD.USD_PM.by.GDP_YoY Gold, USD/Troy OUnce, Normalized by GDP Year over Year
7922 LBMAGOLD.USD_PM.by.GDP_YoY5 Gold, USD/Troy OUnce, Normalized by GDP 5 Year over 5 Year
7928 LBMAGOLD.USD_PM.by.GDP_mva200 Gold, USD/Troy OUnce, Normalized by GDP 200 Day MA
7936 GDP.by.GDPDEF_Log Log of Nominal GDP Normalized by GDP def
7937 GDP.by.GDPDEF_mva365 Nominal GDP Normalized by GDP def 365 Day MA
7938 GDP.by.GDPDEF_mva200 Nominal GDP Normalized by GDP def 200 Day MA
7939 GDP.by.GDPDEF_mva050 Nominal GDP Normalized by GDP def 50 Day MA
7945 GSG.Close.by.GDPDEF_SmoothDer Derivative of Smoothed GSCI Commodity-Indexed Trust, Normalized by GDP def
7955 GSG.Close.by.GSPC.Close_SmoothDer Derivative of Smoothed GSCI Commodity-Indexed Trust, Normalized by S&P 500
7967 GDPBYPOPTHM_mva365 GDP/Population 365 Day MA
7993 GSPC.CloseBYMDY.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365) GSPC by MDY
7995 GSPC.CloseBYMDY.Close_SmoothDer Derivative of Smoothed GSPC by MDY
7998 GSPC.CloseBYMDY.Close_mva200 GSPC by MDY 200 Day MA
8003 QQQ.CloseBYMDY.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365) QQQ by MDY
8005 QQQ.CloseBYMDY.Close_SmoothDer Derivative of Smoothed QQQ by MDY
8008 QQQ.CloseBYMDY.Close_mva200 QQQ by MDY 200 Day MA
8009 QQQ.CloseBYMDY.Close_mva050 QQQ by MDY 50 Day MA
8016 GSPC.DailySwing_Log Log of S&P 500 (^GSPC) Daily Swing: (High - Low) / Open
8023 GSPC.Open.by.GDPDEF_Smooth Savitsky-Golay Smoothed (p=3, n=365) S&P 500 (^GSPC) Open divided by GDP deflator
8025 GSPC.Open.by.GDPDEF_SmoothDer Derivative of Smoothed S&P 500 (^GSPC) Open divided by GDP deflator
8028 GSPC.Open.by.GDPDEF_mva200 S&P 500 (^GSPC) Open divided by GDP deflator 200 Day MA
8029 GSPC.Open.by.GDPDEF_mva050 S&P 500 (^GSPC) Open divided by GDP deflator 50 Day MA
8033 GSPC.Close.by.GDPDEF_Smooth Savitsky-Golay Smoothed (p=3, n=365) S&P 500 (^GSPC) Close divided by GDP deflator
8034 GSPC.Close.by.GDPDEF_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) S&P 500 (^GSPC) Close divided by GDP deflator
8035 GSPC.Close.by.GDPDEF_SmoothDer Derivative of Smoothed S&P 500 (^GSPC) Close divided by GDP deflator
8038 GSPC.Close.by.GDPDEF_mva200 S&P 500 (^GSPC) Close divided by GDP deflator 200 Day MA
8039 GSPC.Close.by.GDPDEF_mva050 S&P 500 (^GSPC) Close divided by GDP deflator 50 Day MA
8045 HNFSUSNSA.minus.HSN1FNSA_SmoothDer Derivative of Smoothed Houses for sale - houses sold
8053 MSPUS.times.HOUST_Smooth Savitsky-Golay Smoothed (p=3, n=365) New privately owned units start times median price
8055 MSPUS.times.HOUST_SmoothDer Derivative of Smoothed New privately owned units start times median price
8056 MSPUS.times.HOUST_Log Log of New privately owned units start times median price
8059 MSPUS.times.HOUST_mva050 New privately owned units start times median price 50 Day MA
8063 HOUST.div.POPTHM_Smooth Savitsky-Golay Smoothed (p=3, n=365) Housing starts divided by U.S. population
8065 HOUST.div.POPTHM_SmoothDer Derivative of Smoothed Housing starts divided by U.S. population
8066 HOUST.div.POPTHM_Log Log of Housing starts divided by U.S. population
8068 HOUST.div.POPTHM_mva200 Housing starts divided by U.S. population 200 Day MA
8069 HOUST.div.POPTHM_mva050 Housing starts divided by U.S. population 50 Day MA
8075 MSPUS.times.HNFSUSNSA_SmoothDer Derivative of Smoothed New privately owned 1-family units for sale times median price
8085 MSPUS.times.HSN1FNSA.plusEXHOSLUSM495S_SmoothDer Derivative of Smoothed Median home price times new and existing houses sold
8090 MSPUS.times.HSN1FNSA.plusEXHOSLUSM495S.by.GDP_YoY New and existing home sales volume Year over Year
8095 MSPUS.times.HSN1FNSA.plusEXHOSLUSM495S.by.GDP_SmoothDer Derivative of Smoothed New and existing home sales volume
8106 GSPC.Open_mva050_mva200 S&P 500 50 SMA - 200 SMA
8107 GSPC.Open_mva050_mva200_sig Sell Signal S&P 500 50 SMA - 200 SMA
8108 MULTPLSP500PERATIOMONTH_Mean S&P 500 TTM P/E Average (Excludes Values Greater Than 50)

Equities

Equity indexes normalized by GDP

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

The last two years compare favorably with the period around the late 1950’s. Need to dig into this one.

datay <- "GSPC.Close"
ylim <- c(2000, d.GSPC.max)
my.data <- plotSimilarPeriods(df.data, dfRecession, df.symbols, datay, ylim, i.window = 60)
my.data[[1]]

Look at how the different segments of the market move

datay <- "GSPC.CloseBYMDY.Close_YoY"
ylim <- c(-50, 75)
dtStart = as.Date('1980-01-01')
plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)

datay <- "GSPC.CloseBYMDY.Close"
ylim <- c(0, 20)
dtStart = as.Date('1980-01-01')
plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)

S&P 500 Normalized moving average

Look at moving average relationship by dividing the S&P 500 open price by the 200 day SMA.

datay <- "GSPC.Open_mva200_Norm"
ylim <- c(50, 125)
dt.start = as.Date('2008-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Crossovers

Look at the 50 DMA versus 200 DMA, often used as a technical indicator of market direction.

datay <- "GSPC.Open_mva050_mva200"
ylim <- c(-300, 300)
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStartBackTest)

datay <- "GSPC.Open_mva050_mva200_sig "
ylim <- c(0.0, 1.0)
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStartBackTest)

S&P 500 TTM P/E

Take a look at some of the earnings trends from SilverBlatt’s sheet.

## New names:
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## * `` -> ...2
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## New names:
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## * ...

Take a longer look back at as-reported and operating earnings

Market prices can out-run earnings so take a look at price to earnings.

Focus on some of the more recent activity

S&P 500 Sales

datay <- "MULTPLSP500SALESQUARTER"
ylim <- c(500, 2000)
dt.start <- as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

datay <- "MULTPLSP500SALESQUARTER"
ylim <- c(500, 2000)
dt.start = as.Date('2001-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Unit Profits

The series peaks in the middle of a bull market.

S&P 500 dividends

12-month real dividend per share inflation adjusted November, 2018 dollars. Data courtesy Standard & Poor’s and Robert Shiller.

https://www.quandl.com/data/MULTPL/SP500_DIV_MONTH-S-P-500-Dividend-by-Month

Evaluate year over year dividend growth.

Real value dividend growth.

datay <- "MULTPLSP500DIVMONTH_YoY"
ylim <- c(-40, 20)
dtStart = as.Date('2001-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

S&P 500 dividend yield (12 month dividend per share)/price. Yields following September 2018 (including the current yield) are estimated based on 12 month dividends through September 2018, as reported by S&P. Sources: Standard & Poor’s for current S&P 500 Dividend Yield. Robert Shiller and his book Irrational Exuberance for historic S&P 500 Dividend Yields.

https://www.quandl.com/data/MULTPL/SP500_DIV_YIELD_MONTH-S-P-500-Dividend-Yield-by-Month

datay <- "MULTPLSP500DIVYIELDMONTH"
ylim <- c(0, 12)
dtStart = as.Date('1950-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

datay <- "MULTPLSP500DIVYIELDMONTH"
ylim <- c(1, 4)
dtStart = as.Date('2001-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

S&P 500 Volume

The log of the S&P volume has some interesting patterns, but nothing that seems to help with a recession indicator.

That is one spiky data series. Not sure there is a lot to help us here.

Russell 2000

Take a look at recent activity in the small cap market.

S&P 500 to Rusell 2000

Thirty day movement

Correlation

## Warning in max.default(structure(numeric(0), class = "Date"),
## structure(numeric(0), class = "Date"), : no non-missing arguments to max;
## returning -Inf
## Warning in min.default(structure(numeric(0), class = "Date"),
## structure(numeric(0), class = "Date"), : no non-missing arguments to min;
## returning Inf

S&P 500 to MDY (Mid-cap) 2000 Correlation

datay1 <- "RLG.Open"
ylim1 <- c(0, 2500)

datay2 <- "MDY.Open"
ylim2 <- c(0, 500)

dtStart <- as.Date("1jan2003","%d%b%Y")

w <- 30
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)
## Warning in max.default(structure(numeric(0), class = "Date"),
## structure(numeric(0), class = "Date"), : no non-missing arguments to max;
## returning -Inf
## Warning in min.default(structure(numeric(0), class = "Date"),
## structure(numeric(0), class = "Date"), : no non-missing arguments to min;
## returning Inf

Dividend Stocks

This is an interesting series, they should perform better through the recessions. Unfortunately they are short lived so there is not much data so this is more of a place holder for now.

datay <- "NOBL.Open"
ylim <- c(40, 110)
dt.start <- as.Date('2014-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Margin and option data

NYSE Margin Debt

Taking a look at margin debt. NYXDATA stopped providing NYSE margin debt data on Dec 2017. Data is available from FINRA, but it includes more accounts than the data did for NYXdata. I stitched togeter the data sets: data after Jan 2010 include NYSE+Others, data prior is just NYSE account data scaled up to match the FINRA data.

It tends to creep up when there is a frenzy in the stock market.

datay <- "FINRAMarginDebt_Log"
ylim <- c(5, 15)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Take a close look at recent activity

Sometimes it is more helpful to view year over year growth.

More near-term trend.

Take a look at some of the correlations

datay1 <- "FINRAMarginDebt_YoY"
ylim1 <- c(-100, 100)

datay2 <- "GSPC.Close_YoY"
ylim2 <- c(-100, 100)

dtStart <- as.Date("1jan1995","%d%b%Y")

w <- 90
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)

Comparison to the Russell 2000

datay1 <- "FINRAMarginDebt_YoY"
ylim1 <- c(-100, 100)

datay2 <- "RLG.Close_YoY"
ylim2 <- c(-100, 100)

dtStart <- as.Date("1jan1995","%d%b%Y")

w <- 90
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)

OCC Options Volumes

See what is happening with the options volumes for equities. (From: https://www.theocc.com/webapps/historical-volume-query)

Looks like options on non-equity co-occurs with peaks/troughs?.

Market Volatility

Take a look at some of the indications of market volatility

CBOE VIX

As markets become complacent (low VIX) and high values, peaks often occur.

Compare the VIX to some of the ETF’s out there.

There

Not much predictive in VIX, take a quick look at the smoothed derivative.

S&P Daily Swings

Daily changes in the S&P should correlate well with the VIX.

More of a correlating series than a predictor.

Employment and payrolls

Unemployment rates

Unemployment rates will probably be useful, let’s take a look at the U-3. The data is a little noisy so there is also a smoothed version plotted. There seems to be a relationship between the unemployment rate and the recessions, but it could be a lagging indicator. This will be explored a little bit more later.

Suggested by Charlie and a Wealthian video the 12 month-MA might be helpful to look at.

Looking at the unemployment rate, the eye is drawn to the rise and fall of the data, this suggests that the derivative might be helpful as well. The figure below shows the results, using a Savitzky-Golay FIR filter. It looks like the unemployment rate peaks in the middel of the recession. That peak might be a good buy signal.

Continuing Claims

A good measure of how much unemployment is growing.

Continued claims, also referred to as insured unemployment, is the number of people who have already filed an initial claim and who have experienced a week of unemployment and then filed a continued claim to claim benefits for that week of unemployment. Continued claims data are based on the week of unemployment, not the week when the initial claim was filed

https://fred.stlouisfed.org/series/CCNSA

A good measure of how much unemployment is growing

Initial Claims

A good measure of how much unemployment is growing.

An initial claim is a claim filed by an unemployed individual after a separation from an employer. The claim requests a determination of basic eligibility for the Unemployment Insurance program.

https://fred.stlouisfed.org/series/ICSA

Unemployment rates, year-over-year

Both the headline unemployment and U-6 number changes are similar. During the upswing on the cycle it does look like the headline number falls faster than U-6

The second derivative of the unemployment rate does have zero crossings near the middle point of a recession. This would make it a helpful buy signal for the trading strategy.

Unemployment rates, similar periods

Historically the last two years of record low unemployment appear most similar to the 1971-1973 time frame. Just before inflation took off.

Unemployment rates, U-6 and headline number.

Let’s also take a look at the total unemployed, U-6. It continues to fall as the headline number stabilizes as people return to the work force. An indicator the cycle is beginning to top out.

Difference between U6 and U3 to see how close the economy is getting to full employment.

Unemployment and market bottoms

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Initial jobless claims

We will also take a look at initial jobless claims, this should start to rise just before the unemployment rate.

It looks like the jobless claim tend to peak more towards the end of the recession. It does not seem to be as strong of a sell indicator as the U-3 rate.

Jobless claims have a seasonal component to them. One way to reduce this effect is to calculate year over year growth. That helps some, the peaks seem to be more closely aligned with the middle to end of recessions.

Take a closer look at recent data

## Warning: Removed 1 rows containing missing values (geom_text).
## Warning: Removed 1 rows containing missing values (geom_hline).

Take a look at the percentage of the population looking for work

A bit more recent trend

Unemployment Level

ADP data here. comes out before the official numbers.

Look at the year-over-year change in ADP.

ADP data divided by the population

Payrolls

Look at the BLS data on payrolls. Check the NSA series, then we will look at YoY data.

Hours worked

Sparked by an article at Mises (https://mises.org/wire/how-alexandria-ocasio-cortez-misunderstands-american-poverty), take a look at average weekly hours

The time series is pretty lumpy, plot the YoY change

A more recent look at average weekly hours of production

Industrial Production

Industrial production is also known to fall during an economic downturm, let’s take a look at some of the data from the FRED on industrial production. It does seem to peak prior to a recession so let’s smooth and look at the derivative as it might be a good indicator as well.

Industrial production over the last ten years or so

The derivative isn’t bad, but it sometimes crosses zeros well into a recession. That is less helpful as either a buy or sell indicator. A better measure might year over year (YoY) change.

The year over year change has a similar appearance. The low values at the beginning make the year over year values larger than the more recent values. Seems like it will rank low a reliable indicator.

datay1 <- "INDPRO_YoY"
ylim1 <- c(-20, 12)

datay2 <- "GSPC.Close_YoY"
ylim2 <- c(-100, 50)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Retail Sales

Retail sales, aggregate

Retail sales also change during recession. As the plot below shows, it seems to follow the trend of industrial production. It might be too strongly correlated to add much to the model. The will be examined in the correlation section.

The derivative of retail sales is a little more erratic than is was the industrial products. Looks like it might be helpful to include in the model as well.

Retail sales, aggregate year-over-year

Take a look at year-over-year changes

Retail sales and unemployment correlations

Let’s see how that looks on year over year basis. Interesting to compare to unemployment rates there appears to a correlation over the long term.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

There is some similarity. The rolling correlation shows the inverse relationship prior to a recession.

datay1 <- "RSALESAGG_YoY"
ylim1 <- c(-12.5, 12.5)

datay2 <- "UNEMPLOY_YoY"
ylim2 <- c(-30, 150)

dtStart <- as.Date("1jan1970","%d%b%Y")

w <- 180
corrName <- calcRollingCorr(dfRecession,df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Retail sales correlation and industrial production

Industrial production and retail sales look very similar so the plot below shows the 360 correlation. The corerlation does tend to fall around a recession, although 2008 was so bad that they both fell together. Not sure if it is that useful.

datay1 <- "INDPRO"
ylim1 <- c(40, 125)

datay2 <- "RSALESAGG"
ylim2 <- c(100000, 200000)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 60
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

It is interesting to see the strong correlation; however, I suspect this is due to more to the shape of the trends. How do the YoY correlations look? They are a little less correlated, probably better to use in the machine learning later.

datay1 <- "INDPRO_YoY"
ylim1 <- c(-20, 20)

datay2 <- "RSALESAGG_YoY"
ylim2 <- c(-20, 20)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 30
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Advance Retail Sales

This is an advanced estimate of the retail sales value.

Also take a look at year over year

Retail sales and the labor market

Income

Real Personal Income

Real Personal Income (Excluding Transfer, Annual)

During a recession real personal income falls. In the plot the peaks can be seen prior to each recession.

datay <- "W875RX1"
ylim <- c(3000, 15000)
plotSingleQuickModern(datay, ylim)

The features we are interested in are the peaks and valleys so we’ll use the derivative to get to those. Interesting, there is usually a first zero crossing before a recession and a second during or just after the recession.

Real personal income might have some seasonal variance, but it seems the year over year change tells the same story.

Price and cost measures

This section shows price and cost measures.

Two commonly used indexes are the CPI (consumer price index) and PPI (producer price index). CPI tries to show final prices paid for goods and services by urban U.S. consumers. This index includes sales tax and imports. The PPI attempts to reflect the prices paid at all stages of production, including goods and services purchases as inputs as well as goods and services purchased by consumers from retail and producer sellers. The PPI does not include imports or sales tax. The CPI reflects all rebates and financing plans wherease the PPI reflects only those rebate and financing plans provided by the producer. For example if an automotive manufacturer offers a rebate of $500 and the dealer offers an additional rebate of $500 then the PPI would reflect only the automotive manufacturer rebate, but the CPI would reflect both rebates.

Sources; https://www.bls.gov/opub/hom/pdf/cpihom.pdf and https://www.bls.gov/opub/hom/pdf/ppi-20111028.pdf.

Consumer price index

What does CPI look like?

datay <- "CPIAUCSL"
ylim <- c(0, 300)
plotSingleQuickModern(datay, ylim)

Check out the YoY growth

datay <- "CPIAUCSL_YoY"
ylim <- c(-2, 15)
plotSingleQuickModern(datay, ylim)

CPI to PPI

Suggested by Charlie, it can be helpful to look at the relationship between producer prices and consumer prices.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Producer Price Index (Commodities)

Commodities

Basket

Take a look at some trends of baskets of commodities.

This plot examines commodity performance relative to the GDP deflator

Crude oil

Look at a trend of West Texas Intermediate (WTI)

This is ticker data from yahoo

Take a look at both WTI and Brent crude.

Real price of crude using producer price index for commodities

Gold

As risks increase investors often flock to safe haven assets like gold. An up-tick in prices can indicate investor uncertainty. This can be seen in the nominal price plot around 1980 and again in 2007.

This plots out the real price of gold by two different deflators. PPI corrected price is a little higher, to be expected since CPI also includes the effects of sales tax and imports. The spike in 1980 is especially pronounced in this series.

See how nominal and real prices look year over year. From the long-term view seems like there is little difference in the three series. Although not shown, even over the near-term there is little difference in the series.

See how gold correlates with the VIX. Both gold and VIX should respond to investor axiety, but it doesn’t look like it correlates very well.

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 242 rows containing non-finite values (stat_smooth).

Copper

Dr. Copper has a reputation as an indicator of economic malaise, but it does not seem to have much of a correlation with the recessions. The series below is from CME via Quandl. It has a lot of data so I am also looking at the smoothed version.

Copper is one of the commodities in the PPI so it is a bit of a proxy for how copper is doing relative to the basket of commodities.

The change in prices, year over year, do generally peak prior to a recession. The time and shape of this peak varies, but it still might be helpful. A couple of the large troughs do seem to correlate with the end of the recession. Likely this is because industrial production has also fallen.

There is some correlation between copper and the smooth recession initiator, especially at the end of the recession.

Might be easier to see correlation in a dot plot format.

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 342 rows containing non-finite values (stat_smooth).

This is a legacy series from FRED. It has not been updated in a couple of years so I am assuming it will go away.

Oil Services

Amazing events in the first half of 2020, take a look at those

See how the players are doing

Federal Reserve

The federal reserve has an impact on the economy, here are some data series relating to that.

Little bit closer

datay <- "WALCL"
ylim <- c(0, 10000)
dtStart = as.Date('2003-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Federal Reserve Reverse Repo Agreements

Compare liabilities to reverse repo trends

Take a look at more recent trends

Spiky, might be easier to look at year-over-year

Normalized by GDP

datay <- "WLRRAL.by.GDP"
ylim <- c(0, 4)
dtStart = as.Date('2003-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Overnight Bank Funding Rate

“The overnight bank funding rate is calculated using federal funds transactions and certain Eurodollar transactions. The federal funds market consists of domestic unsecured borrowings in U.S. dollars by depository institutions from other depository institutions and certain other entities, primarily government-sponsored enterprises, while the Eurodollar market consists of unsecured U.S. dollar deposits held at banks or bank branches outside of the United States. U.S.-based banks can also take Eurodollar deposits domestically through international banking facilities (IBFs). The overnight bank funding rate (OBFR) is calculated as a volume-weighted median of overnight federal funds transactions and Eurodollar transactions reported in the FR 2420 Report of Selected Money Market Rates. Volume-weighted median is the rate associated with transactions at the 50th percentile of transaction volume. Specifically, the volume-weighted median rate is calculated by ordering the transactions from lowest to highest rate, taking the cumulative sum of volumes of these transactions, and identifying the rate associated with the trades at the 50th percentile of dollar volume. The published rates are the volume-weighted median transacted rate, rounded to the nearest basis point.” https://www.newyorkfed.org/markets/obfrinfo.

Secured Overnight Financing Rate

“The Secured Overnight Financing Rate (SOFR) is a broad measure of the cost of borrowing cash overnight collateralized by Treasury securities. The SOFR includes all trades in the Broad General Collateral Rate plus bilateral Treasury repurchase agreement (repo) transactions cleared through the Delivery-versus-Payment (DVP) service offered by the Fixed Income Clearing Corporation (FICC), which is filtered to remove a portion of transactions considered “specials” " https://apps.newyorkfed.org/markets/autorates/sofr

Take a look at the variation (99th - 1st percentile)

Reserve Balances with Federal Reserve Banks

Hard to get a sense of these series in the absolute. Take a look relative to GDP.

By double entry book-keeping reserves+loans (assets) = deposit (liabilities). Does that really work?

Correlation Between Reserves and Total Loans

As reserves increase there should be less lending. That correlation generally holds.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Did the reserve balances increase after the 2016 and 2018 drops? Not in the same way. There are some relationships between the equities market and the reserves though.

Explicitly correlate reserve balances and total loans. It is a weak and noisy correlation.

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 990 rows containing non-finite values (stat_smooth).

Interest on excess reserves

Monetary Base

Currency trend, base

This used to trend along with GDP. It doesn’t anymore.

Money supplies

Basic currency trend (currency component of M1)

datay <- "WCURRNS_YoY"
dtStart = as.Date('1980-01-01')
ylim <- c(0, 17)
myplot <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)
myplot

datay <- "WCURRNS_YoY"
dtStart = as.Date('2000-01-01')
ylim <- c(0, 20)
myplot <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)
myplot

The rate of change of money supply could be an indicator of a recession. Let’s see how that compares.

Intervention in the repo market

The federal reserve provides liquidity to the repo market, summary of that action

European central bank

The European central band (ECB) has taken a different path compared to the US Federal Reserve bank.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Federal Debt

The government is a big driver of the economy, let’s see what it is doing in the debt markets.

datay <- "GFDEBTN"
ylim <- c(0, 35000000)
plotSingleQuick(dfRecession, df.data, datay, ylim)

datay <- "GFDEBTN_Log"
ylim <- c(12, 18)
plotSingleQuick(dfRecession, df.data, datay, ylim)

datay <- "GFDEBTN_YoY"
ylim <- c(-10, 25)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Federal debt as percent GDP

datay <- "GFDEGDQ188S"
ylim <- c(30, 150)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Federal deficit as percent GDP

datay <- "FYFSGDA188S"
ylim <- c(-30, 5)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Charlie Hatch has a nice format of deficit versus debt:

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Nonfinancial Corporate Business Debt

What about Nonfinancial corporate business and debt securities? Hopefully this doesn’t follow the business loan trends.

That is crazy steep. Time for a log format, see if that brings out the peaks and troughs. That’s a litte better, it looks like there might be a change in slope prior to the recessions.

The derivative doesn’t seem to be much help. There is not much correlation between the zero crossings and the NEBR recessions.

Debt cycle

This analysis roughly follows the ideas in Big Debt Crises book by Ray Dalio.

Total loans

One business cycle theory describes recessions as a market adjustment to mis-allocated assets, often fueled by an credit expansion. That makes the volume of loans an interesting feature to look at. In the presentation of data it looks like the great recession had the largest impact.

Plotting the year over year growth rate helps pull out those small changes in the early years in the data. Peaks can be seen prior to most recessions.

Zoom in to the last couple of decades

As long term interest rates rise, loans should start to tick down. To check this, the total loans and 10 to 1 year spreads are plotted. This is generally the trend observed.

There is a good correlation between these two variables. This next section plots that correction explicitly.

Total loans as percent of GDP

This is the total loans. I think the picture is too broad to point to a specific sector of the economy. The debt burden assumes interest rates are tied to the 10-year treasury: (TOTLNNSA * DGS10) / 100

Commercial and industral loans

Business loans should slow before the recession (a contraction in credit as rates rise).

Commercial and industrial loans as percent of GDP and and income

Look at business debt normalized by GDP over the entire time series. This ratio often peaks at the mid-point of a recession.

https://www.wsj.com/articles/this-isnt-your-fathers-corporate-bond-market-11590574555

“Bonds are behaving more like bank debt, which tends to remain stable or even increase at the onset of recessions, as lenders keep distressed clients afloat—and only later turn off the taps. This was confirmed by a recent report from the Bank for International Settlements. It also found a tight link between this lending cycle and the “real” economy’s booms and busts."

I assume that interest is related to the 10-year treasure: (TOTCINSA * DGS10) / 100

Farm loans

See how the farming sector is fairing.

Real estate loans

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

This gives a big picture, but makes it hard to connect the loans with the income needed to cover those loans. In the next section, loans will be broken up by commercial and residential.

Real Estate (Residential)

In absolute terms the mortgages have increased, but it does not appear to be out of line with the overall economy.

Normalized by GDP it is easier to see the peak in 2008 and that loan levels appear reasonable at the commercial banks. I updated this plot to include the estimated single-family home sales volume to give a sense of percentage of home sales that are cash.

Maybe the GSE’s are making loans. Take a look at the total mortgages from Z.1 as a percentage of GDP. That does not look too far off trend (ignoring that peak in 2008).

I am assuming that personal income is paying for the mortgages.

Real estate (residential) as percent of GDP and and income

## Warning: Removed 1 rows containing missing values (geom_text).

How do the number of starts compare to population?

Consumer loans

Focusing on the consumer sector the growth in debt and incomes can be directly compared. Personal income, as a percent of GDP, remains nearly constant. It is not uncommon for the personal income to rise prior to a recession. Likely this reflect increasing asset prices and market returns. Also interesting to see the loans pick up after interest rates dropped in 1982.

Consumer loans as percent of GDP and and income

Take a closer look since the 2008 recession. Looks like loans are starting to slow as the interest burden rises and incomes remain stable. There are some anomolies in the A065RC1A027NBEA data series because it only updates onces a year. the PI series updates once a month but is noisier and seasonally adjusted. It also shows incomes rising in the middle of the 2008 recession, which doesn’t seem to be accurate.

## Warning: Removed 1 rows containing missing values (geom_text).
## Removed 1 rows containing missing values (geom_text).
## Warning: Removed 1 rows containing missing values (geom_hline).

Repo market

This market went through some stress in 2008, it is happening again so setup some plots to watch it.

Nonfincial corporate business security repo asset level

Bonds

T-Bills and Yield Curve

Speaking of loans, interest rates also play into this. This analysis will focus on treasure bills. The 3-month is plotted below. The yield flattens before a recession as investors go long on bonds and short on equities.

datay <- "TB3MS"
datay.aux <- "DTB3"
ylim <- c(0, 20)
p1 <- plotSingleQuickModern(datay, ylim)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

datay <- "TB3MS"
datay.aux <- "DTB3"
ylim <- c(0, 6.0)
dtStart = as.Date('2017-01-01')
p1 <- plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

# {r bond3monthlibor, echo=FALSE } # # datay <- "TB3MS" # datay_aux <- "USD1MTD156N" # ylim <- c(0, 12) # dtStart = as.Date('1985-01-01') # myPlot <- plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", # getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE) # myPlot <- myPlot + geom_line(data=df.data, aes_string(x="date", y=datay_aux, colour=shQuote(datay_aux)), na.rm = TRUE) # # myPlot # # Check out LIBOR and fed funds rate

The 1-year is plotted below. The yield flattens before a recession as investors go long on bonds and short on equities.

datay <- "DGS10"
datay.aux <- "TNX.Close"
ylim <- c(0, 20)
p1 <- plotSingleQuickModern(datay, ylim)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

Close in, the trend towards inversion be more easily seen. I am also comparing data from the CBOE as well as FRED.

Bond yields are a good proxy for interest rates. As rates rise the theory goes that loans should decrease (inverse correlation).

And a longer window

The yield curve (30 year bond rate minus the 10 year bond rate) may not be a good recession indicator, but a collapse is not good (https://blogs.wsj.com/moneybeat/2018/04/30/theres-more-than-one-part-of-the-yield-curve-getting-flatter/).

The yield curve (10 year bond rate minus the 1 year bond rate) seems to a good indicator of an oncoming recession. It could be a buy indicator by itself.

More recent data

Just the last 24 months or so.

Plot the 10 Year to 3 month over a few decades to see what the outling cases look like

The last two year compare favorably with the period around the 2015-2016 turndown, driven primarily by slowing of the Chinese GDP. Not a debt-driven cycle.

This plot format was suggested by a mises.org article (https://mises.org/wire/yield-curve-accordion-theory), but they only went back to 1988. The date seemed arbitrary so I went back further in time.

Take a look at more recent data

Try looking at a 1-year average of the above time series

High quality bonds

datay <- "AAA"
ylim <- c(1.5, 10)
dtStart = as.Date('1997-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High quality bonds to 10-year treasury

High quality bonds long-term trend.

datay <- "DGS10ByAAA"
ylim <- c(1, 6.0)
dtStart = as.Date('1967-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High quality bonds near-term trend.

datay <- "DGS10ByAAA"
ylim <- c(1, 6.0)
dtStart = as.Date('2007-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High yield spread

“This data represents the Option-Adjusted Spread (OAS) of the ICE BofAML US Corporate A Index, a subset of the ICE BofAML US Corporate Master Index tracking the performance of US dollar denominated investment grade rated corporate debt publicly issued in the US domestic market. This subset includes all securities with a given investment grade rating A. The ICE BofAML OASs are the calculated spreads between a computed OAS index of all bonds in a given rating category and a spot Treasury curve. An OAS index is constructed using each constituent bond‚Äôs OAS, weighted by market capitalization. When the last calendar day of the month takes place on the weekend, weekend observations will occur as a result of month ending accrued interest adjustments.”

  • ICE Benchmark Administration Limited (IBA), ICE BofAML US Corporate A Option-Adjusted Spread [BAMLC0A3CA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/BAMLC0A3CA, July 4, 2019.
datay <- "BAMLC0A3CA"
ylim <- c(0, 7)
dtStart = as.Date('1997-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Municipal bond market

Suggest by a WSJ article, change in volume for high-risk muni’s. Doesn’t look like there is much too it yet.

https://www.wsj.com/articles/risky-municipal-bonds-are-on-a-hot-streak-11558949401?mod=hp_lead_pos3

datay <- "HYMB.Close"
ylim <- c(40, 62)
dtStart = as.Date('2011-01-01')
p1 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

datay <- "HYMB.Volume"
ylim <- c(0, 1750000)
p1.vol <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )


datay <- "GSPC.Open"
datay_aux <- "GSPC.Close"
ylim <- c(1500, d.GSPC.max )
p2 <-
  plotSingle(
    dfRecession,
    df.data,
    "date",
    datay,
    getPlotTitle(df.symbols, datay),
    "Date",
    getPlotYLabel(df.symbols, datay),
    c(dtStart, Sys.Date()),
    ylim,
    TRUE
  )

p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )


grid.arrange(p1,
             p1.vol,
             p2,
             ncol = 1,
             top = "High Yield Muni's and S&P Price")

Total Loans and yield curve correlation

This relationship was suggest by Charlie and it is an interesting one. As the yield curve flattens (10-year and 1-year rates converge), total loans grow. The generalization is not always accurate, but it does fit.

## `geom_smooth()` using formula 'y ~ x'

I wanted to see how this looked compared to the 3 month

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 282 rows containing non-finite values (stat_smooth).

Consumer loans and yield curve correlation

Compared to business loans, consumer loans seem to have to response to the 10Y to 3M yield curve.

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 311 rows containing non-finite values (stat_smooth).

Business loans and yield curve correlation

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 104 rows containing non-finite values (stat_smooth).

That’s pretty good correlation. Let’s see what the rolling correlation looks like.

datay1 <- "TOTLNNSA_YoY"
ylim1 <- c(-10, 20)

datay2 <- "DGS10TO1"
ylim2 <- c(-5, 10)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

datay1 <- "TOTLNNSA_YoY"
ylim1 <- c(-10, 20)

datay2 <- "DGS10TO1"
ylim2 <- c(-5, 10)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 720
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

One other items, let’s see how loans do versus the federal funds rate

## `geom_smooth()` using formula 'y ~ x'

Baker Hughes Rig Count

BEA Supplemental Estimates, Motor Vehicles

Definitions

Autos–all passenger cars, including station wagons.
Light trucks–trucks up to 14,000 pounds gross vehicle weight, including minivans and
sport utility vehicles. Prior to the 2003 Benchmark Revision light trucks were up to 10,000 pounds.
Heavy trucks–trucks more than 14,000 pounds gross vehicle weight.
Prior to the 2003 Benchmark Revision heavy trucks were more than 10,000 pounds.
Domestic sales–United States (U.S.) sales of vehicles assembled in the U.S., Canada, and Mexico.
Foreign sales–U.S. sales of vehicles produced elsewhere.
Domestic auto production–Autos assembled in the U.S.
Domestic auto inventories–U.S. inventories of vehicles assembled in the U.S., Canada, and Mexico.

TAble 6 - Light Vehicle and Total Vehicle Sales

Auto sales

A WSJ article suggested that auto sales might be a good indicator so bring that to the mix. It does have troughs that correlate with recessions

There might be some seasonal variance in the auto sales so lets take a look at the year over year. The data is pretty noisy, it probably will not make a very good indicator.

BEA Gross Domestic Product

Data in this section come from the Bureau of Economic Analysis.

Table 1.1.5. Gross Domestic Product

[Billions of dollars] Seasonally adjusted at annual rates

A191RC: Gross Domestic Product - Line 1

GDP numbers tend to lag so this series is truly an afterthought. But it does have some correlation with the recessions.

GDP does not reflect the capacity of the economy nor the efficiency. Shrinking capacity and lower prices at constant volumes would indicate improvements in effeciency/productivity which is good for the economy, but does not move the GDP upward.

Looks like the year over year change on the GDP should correlate well with unemployment.

Table 1.1.9. Implicit Price Deflators for Gross Domestic Product

[Index numbers, 2012=100] Seasonally adjusted

A191RD: Gross Domestic Product - Line 1

This is GDP price deflator series.

GDP normalized by CPI

Normalize GDP by CPI

Economic yield curve (GDP to 1-year treasury)

GDP versus the yield on the 1-year. This series was prompted by an article suggesting that the “economic yield curve” should be used to indicate a recession rather than an inverted yield curve. Less of indicator and more of concurrent confirmation of recession. Not sure why they would be related either.

Economic yield curve (GDP to 3-month treasury)

Same idea as above, but applied the 3-month treasury.This one has fewer false triggers, but is not as helpful as 10Y to 3M spread in predicting a recession.

A824RC: National defense Federal Gov’t Expenditures - Line 24

U.S. Bureau of Economic Analysis, Federal Government: National Defense Consumption Expenditures and Gross Investment [FDEFX], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/FDEFX, April 6, 2021.

A825RC: Nondefense Federal Gov’t Expenditures - Line 25

U.S. Bureau of Economic Analysis, Federal Government: Nondefense Consumption Expenditures and Gross Investment [FNDEFX], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/FNDEFX, April 6, 2021.

Table 6.16D. Corporate Profits by Industry

Select series from Table 6.16D

A051RC: Corporate profits with inventory and capital consumption adjustment

From BEA’s documentation (https://www.bea.gov/media/5671):

“BEA’s featured measure of corporate profits — profits from current production - provides a comprehensive and consistent economic measure of the income earned by all U.S. corporations. As such, it is unaffected by changes in tax laws, and it is adjusted for nonreported and misreported income. It excludes dividend income, capital gains and losses, and other financial flows and adjustments, such as deduction for “bad debt.” Thus, the NIPA measure of profits is a particularly useful analytical measure of the health of the corporate sector. For example, in contrast to other popular measures of corporate profits, the NIPA measure did not show the large run-up in profits during the late 1990s that was primarily attributable to capital gains.

Profits after tax with IVA and CCAdj is equal to corporate profits with IVA and CCAdj less taxes on corporate income. It provides an after-tax measure of profits from current production."

Data is Line 1 of Table 6.16D

A053RC: Corporate profits without inventory and capital consumption adjustment

Profits look a bit flat over the last several years in this series.

Table 2.6. Personal Income and Its Disposition, Monthly

Billions of dollars; months are seasonally adjusted at annual rates.

A065RC Personal Income - Line 1

BEA Account Code: A065RC

Personal income is the income that persons receive in return for their provision of labor, land, and capital used in current production and the net current transfer payments that they receive from business and from government.25 Personal income is equal to national income minus corporate profits with inventory valuation and capital consumption adjustments, taxes on production and imports less subsidies, contributions for government social insurance, net interest and miscellaneous payments on assets, business current transfer payments (net), current surplus of government enterprises, and wage accruals less disbursements, plus personal income receipts on assets and personal current transfer receipts. A Guide to the National Income and Product Accounts of the United States (NIPA) - (http://www.bea.gov/national/pdf/nipaguid.pdf)

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Income [PI], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PI, July 11, 2019.

DPCERC: Personal consumption expenditures (PCE) - Table 2.1, Line 29

BEA Account Code: DPCERC Personal consumption expenditures (PCE) is the primary measure of consumer spending on goods and services in the U.S. economy. 1 It accounts for about two-thirds of domestic final spending, and thus it is the primary engine that drives future economic growth. PCE shows how much of the income earned by households is being spent on current consumption as opposed to how much is being saved for future consumption. -https://www.bea.gov/system/files/2019-12/Chapter-5.pdf

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Consumption Expenditures [PCE], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PCE, June 12, 2020

DPCERG: Personal consumption expenditures Price Index (PCEPI) - Table 2.1, Line 29

BEA Account Code: DPCERG The gross domestic product price index measures changes in prices paid for goods and services produced in the United States, including those exported to other countries. Prices of imports are excluded. The gross domestic product implicit price deflator, or GDP deflator, basically measures the same things and closely mirrors the GDP price index, although the two price measures are calculated differently. The GDP deflator is used by some firms to adjust payments in contracts.

The gross domestic purchases price index is BEA’s featured measure of inflation for the U.S. economy overall. It measures changes in prices paid by consumers, businesses, and governments in the United States, including the prices of the imports they buy.

BEA’s closely followed personal consumption expenditures price index, or PCE price index, is a narrower measure. It looks at the changing prices of goods and services purchased by consumers in the United States. It’s similar to the Bureau of Labor Statistics’ consumer price index for urban consumers. The two indexes, which have their own purposes and uses, are constructed differently, resulting in different inflation rates.

The PCE price index is known for capturing inflation (or deflation) across a wide range of consumer expenses and for reflecting changes in consumer behavior. For example, if the price of beef rises, shoppers may buy less beef and more chicken. Also, BEA revises previously published PCE data to reflect updated information or new methodology, providing consistency across decades of data that’s valuable for researchers. The PCE price index is used primarily for macroeconomic analysis and forecasting. -https://www.bea.gov/resources/learning-center/what-to-know-prices-inflation

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Consumption Expenditures: Chain-type Price Index [PCEPI], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PCEPI, April 25, 2021.

A072RC: Personal Savings Rate - Line 35

Consumers tend to pull down their savings rates as unemployment decreases and market conditions improve. This series has tended to be unreliable due to the size of revisions during the comprehensive update carried out by the BEA. The last update on this series moved the rate from 4.2 to 6.7 percent.

(https://www.bloomberg.com/news/articles/2018-07-27/americans-have-been-saving-much-more-than-thought-new-data-show)

BEA Account Code: A072RC Personal saving as a percentage of disposable personal income (DPI), frequently referred to as “the personal saving rate,” is calculated as the ratio of personal saving to DPI. Personal saving is equal to personal income less personal outlays and personal taxes; it may generally be viewed as the portion of personal income that is used either to provide funds to capital markets or to invest in real assets such as residences.(https://www.bea.gov/national/pdf/all-chapters.pdf) A Guide to the National Income and Product Accounts of the United States (NIPA).

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Saving Rate [PSAVERT], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PSAVERT, July 9, 2019.

Take a closer look at the last decade

The relationship between personal savings and unemployment (U-3) can be better visualized with a scatter plot

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 195 rows containing non-finite values (stat_smooth).

The fit does not explain most of what is in the plot. Lets take a look at the rolling correlation.

datay1 <- "UNRATE"
ylim1 <- c(2, 12)

datay2 <- "PSAVERT"
ylim2 <- c(0, 35)

dtStart <- as.Date("1jan1985","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Personal savings to household net worth

A relationship between personal savings and household networth can be seen in a scatter plot. This was suggested by a WSJ article (https://blogs.wsj.com/dailyshot/2018/02/23/the-daily-shot-reasons-for-declining-u-s-household-savings-rate/).

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 1049 rows containing non-finite values (stat_smooth).

U.S. Census Bureau

U.S. International Trade in Goods and Services (FT900)

U.S. Bureau of Economic Analysis and U.S. Census Bureau, U.S. Imports of Goods by Customs Basis from China [IMPCH], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/IMPCH, October 5, 2019.

New Houses Sold and For Sale by Stage of Construction and Median Number of Months on Sales Market

Read an article suggesting that housing sales and sales growth could be useful. FRED only has new home data so start there.

datay <- "HSN1FNSA"
ylim <- c(0, 200)
dtStart = as.Date('1964-01-01')
p1 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "HNFSUSNSA"
ylim <- c(0, 600)
p2 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "HNFSUSNSA.minus.HSN1FNSA"
ylim <- c(0, 600)
p3 <-
  plotSingle(
    dfRecession,
    df.data,
    "date",
    datay,
    getPlotTitle(df.symbols, datay),
    "Date",
    getPlotYLabel(df.symbols, datay),
    c(dtStart, Sys.Date()),
    ylim,
    TRUE
  )

grid.arrange(p1,
             p2,
             p3,
             ncol = 1,
             top = "New Housing Sales")

New housing yoy

New Privately-Owned Housing Units Authorized in Permit-Issuing Places

As provided by the Census, start occurs when excavation begins for the footings or foundation of a building. All housing units in a multifamily building are defined as being started when this excavation begins. Beginning with data for September 1992, estimates of housing starts include units in structures being totally rebuilt on an existing foundation.

Suggested Citation: U.S. Census Bureau and U.S. Department of Housing and Urban Development, Housing Starts: Total: New Privately Owned Housing Units Started [HOUST], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/HOUST, June 13, 2020.

Take a look at privately owned starts

New Privately-Owned Houses Sold and For Sale

Suggested Citation: U.S. Census Bureau and U.S. Department of Housing and Urban Development, Median Sales Price of Houses Sold for the United States [MSPUS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/MSPUS, June 13, 2020.

Finally, take a look at starts times the median price

Durable Goods

Suggested Citation: U.S. Census Bureau, Manufacturers’ New Orders: Durable Goods [UMDMNO], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/UMDMNO, April 26, 2021.

Durable goods, not seasonally adjusted, divided by GDP

Durable goods, seasonally adjusted, divided by GDP

Federal reserve board H.8: Assets and Liabilities of Commercial Banks in the United States

Page 4: Not Seasonally adjusted, billions of dollars

Commercial and industrial loans, all commercial banks - Line 10

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

Suggested Citation: Board of Governors of the Federal Reserve System (US), Commercial and Industrial Loans, All Commercial Banks [BUSLOANS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/BUSLOANS, July 11, 2019.

Taking a look at the difference in SA and NSA series. Seasonal adjustments do vary, but do not seem to be related to recessions.

The raw series is just too steep for any kind of machine learnine. This needs to be converted to log scale.

That’s a little better, let’s see what the smoothed derivative looks like.

That is odd…looks like this doesn’t cross zero unless we are getting close to, or into, a recession. The year over year tells about the same story. Might be a good indication of the end of a recession.

Consumer loans, all commercial banks - Line 20

Suggested Citation: Board of Governors of the Federal Reserve System (US), Consumer Loans, All Commercial Banks [CONSUMERNSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/CONSUMERNSA, July 11, 2019.

That spike in consumer loans is due to

“April 9, 2010 (Last revised September 23, 2011): As of the week ending March 31, 2010, domestically chartered banks and foreign-related institutions had consolidated onto their balance sheets the following assets and liabilities of off-balance-sheet vehicles, owing to the adoption of FASB’s Financial Accounting Statements No. 166 (FAS 166),”Accounting for Transfers of Financial Assets," and No. 167 (FAS 167), “Amendments to FASB Interpretation No. 46(R).”

This included a consumer loans, credit cards and other revolving plans change of $321.9B. That was a lot of off-balance-sheet bank assets.

Deposits, All Commercial Banks, all commercial banks - Line 34

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

Suggested Citation: Board of Governors of the Federal Reserve System (US), Deposits, All Commercial Banks [DPSACBW027SBOG], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/DPSACBW027SBOG, May 14, 2020.

Federal reserve board Z.1: Financial Accounts of the United States

From the FRED website (https://fred.stlouisfed.org/release?rid=52):

"The Financial Accounts (formerly known as the Flow of Funds accounts) are a set of financial accounts used to track the sources and uses of funds by sector. They are a component of a system of macroeconomic accounts including the National Income and Product accounts (NIPA) and balance of payments accounts, all of which serve as a comprehensive set of information on the economy’s performance.(1) Some important inferences that can be drawn from the Financial accounts are the financial strength of a given sector, new economic trends, changes in the composition of wealth, and development of new financial instruments over time.(1)

Sectors are compiled into three categories: households, nonfinancial businesses, and banks. The sources of funds for a sector are its internal funds (savings from income after consumption) and external funds (loans from banks and other financial intermediaries). (1) Funds for a given sector are used for its investments in physical and financial assets. Dividing sources and uses of funds into two categories helps the staff of the Federal Reserve System pay particular attention to external sources of funds and financial uses of funds.(2) One example is whether households are borrowing more from banks—or in other words, whether household debt is rising. Another example might be whether banks are using more of their funds to provide loans to consumers. Transactions within a sector are not shown in the accounts; however, transactions between sectors are.(2) Monitoring the external flows of funds provides insights into a sector’s health and the performance of the economy as a whole.

Data for the Financial accounts are compiled from a large number of reports and publications, including regulatory reports such as those submitted by banks, tax filings, and surveys conducted by the Federal Reserve System.(2) The Financial accounts are published quarterly as a set of tables in the Federal Reserve’s Z.1 statistical release.

  1. Teplin, Albert M. “The U.S. Flow of Funds Accounts and Their Uses.” Federal Reserve Bulletin, July 2001; http://www.federalreserve.gov/pubs/bulletin/2001/0701lead.pdf.
  2. Board of Governors of the Federal Reserve System. “Guide to the Flow of Funds Accounts.” 2000, http://www.federalreserve.gov/apps/fof/."

L.102 Nonfinancial Business

FL102051003.Q: Nonfinancial corporate business; security repurchase agreements; asset

Asset level of nonfinancial business security repo agreements. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL102051003&t=

L.214 Loans

FL894123005.Q: All sectors; total loans; liability

Sum of domestic financial sectors, all sectors, total mortgages, and households/non-profits. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL894123005&t=L.107&bc=L.107:FL793068005&suf=Q

FL793068005.Q: Domestic financial sectors; depository institution loans n.e.c.; asset

Sum of Monetary authority; depository institution loans n.e.c.; asset and Private depository institutions; depository institution loans n.e.c.; asset. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL793068005&t=L.214&suf=Q

FL893169005.Q: All sectors; other loans and advances; liability

Sum of finance, government, and chartered institutions asset levels. https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893169005&t=L.214&suf=Q

FL893065105.Q: All sectors; home mortgages; asset

https://www.federalreserve.gov/apps/fof/DisplayTable.aspx?t=L.214

FL893065405.Q: All sectors; multifamily residential mortgages; asset

https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893065405&t=L.214&suf=Q

FL893065505.Q: All sectors; commercial mortgages; asset

https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893065505&t=L.214&suf=Q

FL153166000.Q: Households and nonprofit organizations; consumer credit; liability

federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL153166000&t=L.214&suf=Q

B.101 Balance Sheet of Households and Nonprofit Organizations

FL152000005.Q: Households and nonprofit organizations; total assets, Level

string.source ID: FL152000005.Q.

FL152090006.Q: Household Net Worth as Percentage of Disposable Personal Income

string.source ID: FL152090006.Q. Household networth tends to fall as a recession start.

Productivity Yield Curve

GDP versus productivity

Manufacturing output and employees

Not sure if these relates to a recession, but fascinating to see how output and employees change with time.

datay <- "OUTMS"
ylim <- c(60, 120)
dtStart = as.Date('1987-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "MANEMP"
ylim <- c(10000, 20000)
dtStart = as.Date('1948-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "PRS30006163"
ylim <- c(40, 120)
dtStart = as.Date('1986-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Shipping volumes might be helpful in determining state of the economy.

datay <- "FRGSHPUSM649NCIS"
ylim <- c(0.8, 1.4)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "FRGSHPUSM649NCIS_YoY"
ylim <- c(-30, 30)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Freight, loosely, moves inversely to the trade deficit.

datay <- "BOPGTB_YoY"
ylim <- c(-30, 30)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

World bank air transportation. Only updated annually so less usefull, but interesting reference to above.

datay <- "WWDIWLDISAIRGOODMTK1"
ylim <- c(0, 250000)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Gross private domestic investment

Spending most certainly tips down prior to a recession. The gross private domestic investment data series, plotted in log format below, show how private investment pulls back prior to recessions.

The change in direction is a little easier to see if the derivative is plotted, first YoY then the smoothed derivative

Velocity

Productivity

Frequency: Quarterly The Productivity and Costs release on August 7, 2003, will reflect the June 2003 benchmark revision to payroll employment. Since employment is now reported on a North American Industry Classification System (NAICS) basis, all of the historical data will be revised. Changes as a consequence of the move to NAICS should not be significant since this release carries data at high levels of aggregation.

Suggested Citation: U.S. Bureau of Labor Statistics, Nonfarm Business Sector: Labor Productivity (Output per Hour) for All Employed Persons [OPHNFB], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/OPHNFB, December 24, 2022.

Date range to match census data

PMI

Industrial Production

This is a look at manufacturing industrial production. The yoY change should be a leading indicator of unemployment.

Housing

Take a look at housing starts. These can drop as rates rise.

Frequency: Monthly

As provided by the Census, start occurs when excavation begins for the footings or foundation of a building. All housing units in a multifamily building are defined as being started when this excavation begins. Beginning with data for September 1992, estimates of housing starts include units in structures being totally rebuilt on an existing foundation.

Suggested Citation: U.S. Census Bureau and U.S. Department of Housing and Urban Development, New Privately-Owned Housing Units Started: Total Units [HOUST], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/HOUST, December 24, 2022.

Housing starts, NSA

HOUST reports at annual rate, but HOUSTNSA just reports the monthly numbers. I scale up the NSA to the annual rate.

Units: Thousands of Units, Not Seasonally Adjusted

Frequency: Monthly

Suggested Citation: U.S. Census Bureau and U.S. Department of Housing and Urban Development, New Privately-Owned Housing Units Started: Total Units [HOUSTNSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/HOUSTNSA, December 24, 2022.

Case-schiller price index

Population data

Many of the economic series can be better understood if normalized by population. Basic population and worker data from FRED.

Population to GDP

Look at GDP divided by CPI per person. It flattens and even dips a little prior to a recession. Might be worth looking at the derivative of this series.

That is worth a closer look

datay1 <- "GDPBYCPIAUCSLBYPOPTHM_SmoothDer"
ylim1 <- c(-5, 5)

datay2 <- "RecInit_Smooth"
ylim2 <- c(0, 1)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 30
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Correlation Study

Detailed correlations are explored above. Before concluding, let’s take a look at some overall correlation values to see if anything pops out.

Commodities

As mentioned above, copper, year over year, has some correlation with the recession initiation. It could be useful.

GDP Series

GDP, normalized first by CPI and then by population, looks like it migh correlate inversely with the recession indicators

Financials

Let’s see where we are so far. The correlation plot confirms some of the speculation above. The S&P 500 (GSPC.Open) is well correlated with industrial production (INDPRO), business loans (BUSLOANS), total loans (TOTLNNSA) , and nonfinancial corporate business debt (NCBDBIQ027S).

In this case, I want and indicator that rises prior to a recession. It looks like the unemployment rate (UNRATE), real personal income (W875RX1), and the yield curve (DGS10TO1) are all inversely correlated with the recession initiation indicator.

I thought the modified recession initiation would be a harder match, but there are quite a few correlated variables. Lets take a look at some of those in more detail

Complete list of symbols

Since it is tedious to do this one at a time, all the symbols were entered into a data frame, loaded, and aggregated together in a single xts object.

This is the complete list of symbol names and sources used in the project.